Add various language bindings for streaming T-one Russian ASR models (#2576)

This PR adds support for streaming T-one Russian ASR models across various language bindings in the sherpa-onnx library. The changes enable T-one CTC (Connectionist Temporal Classification) model integration by adding new configuration structures and example implementations.

- Introduces OnlineToneCtcModelConfig structures across all language bindings (C, C++, Swift, Java, Kotlin, Go, etc.)
- Adds T-one CTC model support to WASM implementations for both ASR and keyword spotting
- Provides comprehensive example implementations demonstrating T-one model usage in multiple programming languages

@@ -4,6 +4,36 @@ set -ex
 
 cd dart-api-examples
 
+pushd streaming-asr
+
+echo '----------streaming T-one ctc----------'
+./run-t-one-ctc.sh
+rm -rf sherpa-onnx-*
+
+echo '----------streaming zipformer ctc HLG----------'
+./run-zipformer-ctc-hlg.sh
+rm -rf sherpa-onnx-*
+
+echo '----------streaming zipformer ctc----------'
+./run-zipformer-ctc.sh
+rm -rf sherpa-onnx-*
+
+echo '----------streaming zipformer transducer----------'
+./run-zipformer-transducer-itn.sh
+./run-zipformer-transducer.sh
+rm -f itn*
+rm -rf sherpa-onnx-*
+
+echo '----------streaming NeMo transducer----------'
+./run-nemo-transducer.sh
+rm -rf sherpa-onnx-*
+
+echo '----------streaming paraformer----------'
+./run-paraformer.sh
+rm -rf sherpa-onnx-*
+
+popd # streaming-asr
+
 pushd tts
 
 echo '----------matcha tts----------'
@@ -167,29 +197,3 @@ popd
 pushd keyword-spotter
 ./run-zh.sh
 popd
-
-pushd streaming-asr
-
-echo '----------streaming zipformer ctc HLG----------'
-./run-zipformer-ctc-hlg.sh
-rm -rf sherpa-onnx-*
-
-echo '----------streaming zipformer ctc----------'
-./run-zipformer-ctc.sh
-rm -rf sherpa-onnx-*
-
-echo '----------streaming zipformer transducer----------'
-./run-zipformer-transducer-itn.sh
-./run-zipformer-transducer.sh
-rm -f itn*
-rm -rf sherpa-onnx-*
-
-echo '----------streaming NeMo transducer----------'
-./run-nemo-transducer.sh
-rm -rf sherpa-onnx-*
-
-echo '----------streaming paraformer----------'
-./run-paraformer.sh
-rm -rf sherpa-onnx-*
-
-popd # streaming-asr

@@ -10,6 +10,17 @@ arch=$(node -p "require('os').arch()")
 platform=$(node -p "require('os').platform()")
 node_version=$(node -p "process.versions.node.split('.')[0]")
 
+echo "----------streaming ASR T-one----------"
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+
+node ./test_asr_streaming_t_one_ctc.js
+
+rm -rf sherpa-onnx-streaming-t-one-russian-2025-09-08
+
+echo "----------KittenTTS----------"
+
 curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/kitten-nano-en-v0_1-fp16.tar.bz2
 tar xf kitten-nano-en-v0_1-fp16.tar.bz2
 rm kitten-nano-en-v0_1-fp16.tar.bz2

@@ -9,6 +9,13 @@ git status
 ls -lh
 ls -lh node_modules
 
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+node ./test-online-t-one-ctc.js
+
+rm -rf sherpa-onnx-streaming-t-one-russian-2025-09-08
+
 curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/kitten-nano-en-v0_1-fp16.tar.bz2
 tar xf kitten-nano-en-v0_1-fp16.tar.bz2
 rm kitten-nano-en-v0_1-fp16.tar.bz2

@@ -9,6 +9,9 @@ ls -lh
 
 ./run-test-version.sh
 
+./run-decode-file-t-one-streaming.sh
+rm -rf sherpa-onnx-streaming-*
+
 ./run-compute-speaker-embeddings.sh
 rm -fv *.wav *.onnx
 

@@ -75,6 +75,36 @@ jobs:
             otool -L ./install/lib/libsherpa-onnx-c-api.dylib
           fi
 
+      - name: Test T-one
+        shell: bash
+        run: |
+          name=streaming-t-one-ctc-c-api
+          gcc -o $name ./c-api-examples/$name.c \
+            -I ./build/install/include \
+            -L ./build/install/lib/ \
+            -l sherpa-onnx-c-api \
+            -l onnxruntime
+
+          ls -lh $name
+
+          if [[ ${{ matrix.os }} == ubuntu-latest || ${{ matrix.os }} == ubuntu-22.04-arm ]]; then
+            ldd ./$name
+            echo "----"
+            readelf -d ./$name
+          fi
+
+          curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+          tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+          rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+
+          export LD_LIBRARY_PATH=$PWD/build/install/lib:$LD_LIBRARY_PATH
+          export DYLD_LIBRARY_PATH=$PWD/build/install/lib:$DYLD_LIBRARY_PATH
+
+          ./$name
+
+          rm $name
+          rm -rf sherpa-onnx-streaming-t-one-russian-2025-09-08
+
       - name: Test KittenTTS
         shell: bash
         run: |
@@ -530,7 +560,8 @@ jobs:
           rm -rf sherpa-onnx-*
 
       - name: Test ffmpeg
-        if: matrix.os == 'macos-latest'
+        # if: matrix.os == 'macos-latest'
+        if: false
         shell: bash
         run: |
           brew install ffmpeg

@@ -78,6 +78,40 @@ jobs:
             otool -L ./install/lib/libsherpa-onnx-cxx-api.dylib
           fi
 
+      - name: Test T-one
+        shell: bash
+        run: |
+          name=streaming-t-one-ctc-cxx-api
+          g++ -std=c++17 -o $name ./cxx-api-examples/$name.cc \
+            -I ./build/install/include \
+            -L ./build/install/lib/ \
+            -l sherpa-onnx-cxx-api \
+            -l sherpa-onnx-c-api \
+            -l onnxruntime
+
+          ls -lh $name
+
+          if [[ ${{ matrix.os }} == ubuntu-latest || ${{ matrix.os }} == ubuntu-22.04-arm ]]; then
+            ls -lh ./$name
+            ldd ./$name
+            echo "----"
+            readelf -d ./$name
+          fi
+
+          curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+          tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+          rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+
+          echo "---"
+
+          export LD_LIBRARY_PATH=$PWD/build/install/lib:$LD_LIBRARY_PATH
+          export DYLD_LIBRARY_PATH=$PWD/build/install/lib:$DYLD_LIBRARY_PATH
+
+          ./$name
+
+          rm -rf sherpa-onnx-streaming-t-one-russian-2025-09-08
+          rm -v ./$name
+
       - name: Test KittenTTS
         shell: bash
         run: |

@@ -126,6 +126,43 @@ jobs:
             cp -v ../sherpa-onnx/pascal-api/*.pas ../pascal-api-examples/vad-with-non-streaming-asr
           fi
 
+      - name:  Run Pascal test (Streaming ASR)
+        shell: bash
+        run: |
+          export PATH=/c/lazarus/fpc/3.2.2/bin/x86_64-win64:$PATH
+
+          cd ./pascal-api-examples
+
+          pushd streaming-asr
+
+          ./run-t-one-ctc.sh
+          rm -rf sherpa-onnx-*
+          echo "---"
+
+          ./run-zipformer-transducer.sh
+          rm -rf sherpa-onnx-*
+          echo "---"
+
+          ./run-nemo-transducer.sh
+          rm -rf sherpa-onnx-*
+          echo "---"
+
+          if [[ ${{ matrix.os }} != 'windows-latest' ]]; then
+            ./run-paraformer.sh
+            rm -rf sherpa-onnx-*
+            echo "---"
+
+            ./run-zipformer-ctc.sh
+            echo "---"
+
+            ./run-zipformer-ctc-hlg.sh
+            rm -rf sherpa-onnx-*
+            echo "---"
+          fi
+
+          ls -lh
+          popd
+
       - name:  Run Pascal test (VAD test)
         shell: bash
         run: |
@@ -321,36 +358,3 @@ jobs:
           echo "---"
           ls -lh
           popd
-
-      - name:  Run Pascal test (Streaming ASR)
-        shell: bash
-        run: |
-          export PATH=/c/lazarus/fpc/3.2.2/bin/x86_64-win64:$PATH
-
-          cd ./pascal-api-examples
-
-          pushd streaming-asr
-
-          ./run-zipformer-transducer.sh
-          rm -rf sherpa-onnx-*
-          echo "---"
-
-          ./run-nemo-transducer.sh
-          rm -rf sherpa-onnx-*
-          echo "---"
-
-          if [[ ${{ matrix.os }} != 'windows-latest' ]]; then
-            ./run-paraformer.sh
-            rm -rf sherpa-onnx-*
-            echo "---"
-
-            ./run-zipformer-ctc.sh
-            echo "---"
-
-            ./run-zipformer-ctc-hlg.sh
-            rm -rf sherpa-onnx-*
-            echo "---"
-          fi
-
-          ls -lh
-          popd

@@ -108,6 +108,13 @@ jobs:
           cd ./java-api-examples
           ./run-version-test.sh
 
+      - name:  Run java test (Streaming T-one)
+        shell: bash
+        run: |
+          cd ./java-api-examples
+          ./run-streaming-decode-file-tone-ctc.sh
+          rm -rf sherpa-onnx-streaming-t-one-*
+
       - name:  Run java test (Nemo Canary)
         shell: bash
         run: |

@@ -140,19 +140,6 @@ jobs:
           name: ${{ matrix.os }}-libs
           path: to-upload/
 
-      - name: Test non-streaming decoding files with NeMo Canary
-        shell: bash
-        run: |
-          cd scripts/go/_internal/non-streaming-canary-decode-files/
-          ls -lh
-          go mod tidy
-          cat go.mod
-          go build
-          ls -lh
-
-          ./run.sh
-          rm -rf sherpa-onnx-nemo-*
-
       - name: Test streaming decoding files
         shell: bash
         run: |
@@ -163,6 +150,9 @@ jobs:
           go build
           ls -lh
 
+          echo "Test T-one CTC"
+          ./run-t-one-ctc.sh
+
           echo "Test zipformer2 CTC"
           ./run-zipformer2-ctc-with-hr.sh
           ./run-zipformer2-ctc.sh
@@ -179,6 +169,21 @@ jobs:
           ./run-paraformer.sh
           rm -rf sherpa-onnx-streaming-paraformer-bilingual-zh-en
 
+      - name: Test non-streaming decoding files with NeMo Canary
+        shell: bash
+        run: |
+          cd scripts/go/_internal/non-streaming-canary-decode-files/
+          ls -lh
+          go mod tidy
+          cat go.mod
+          go build
+          ls -lh
+
+          ./run.sh
+          rm -rf sherpa-onnx-nemo-*
+
+
+
       - name: Test non-streaming decoding files
         shell: bash
         run: |

@@ -150,3 +150,4 @@ kitten-nano-en-v0_1-fp16
 *.jar
 vocab.json
 *.so
+sherpa-onnx-streaming-t-one-russian-2025-09-08

@@ -44,6 +44,9 @@ target_link_libraries(speaker-identification-c-api sherpa-onnx-c-api)
 add_executable(streaming-hlg-decode-file-c-api streaming-hlg-decode-file-c-api.c)
 target_link_libraries(streaming-hlg-decode-file-c-api sherpa-onnx-c-api)
 
+add_executable(streaming-t-one-ctc-c-api streaming-t-one-ctc-c-api.c)
+target_link_libraries(streaming-t-one-ctc-c-api sherpa-onnx-c-api)
+
 add_executable(audio-tagging-c-api audio-tagging-c-api.c)
 target_link_libraries(audio-tagging-c-api sherpa-onnx-c-api)
 

+// c-api-examples/streaming-t-one-ctc-c-api.c
+//
+// Copyright (c)  2025  Xiaomi Corporation
+
+//
+// This file demonstrates how to use streaming T-one with sherpa-onnx's C
+// API.
+// clang-format off
+//
+// wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+// tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+// rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+//
+// clang-format on
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+
+#include "sherpa-onnx/c-api/c-api.h"
+
+int32_t main() {
+  const char *wav_filename =
+      "sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav";
+  const char *model =
+      "sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx";
+  const char *tokens =
+      "sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt";
+  const char *provider = "cpu";
+
+  const SherpaOnnxWave *wave = SherpaOnnxReadWave(wav_filename);
+  if (wave == NULL) {
+    fprintf(stderr, "Failed to read %s\n", wav_filename);
+    return -1;
+  }
+
+  // Zipformer config
+  SherpaOnnxOnlineToneCtcModelConfig t_one_ctc;
+  memset(&t_one_ctc, 0, sizeof(t_one_ctc));
+  t_one_ctc.model = model;
+
+  // Online model config
+  SherpaOnnxOnlineModelConfig online_model_config;
+  memset(&online_model_config, 0, sizeof(online_model_config));
+  online_model_config.debug = 1;
+  online_model_config.num_threads = 1;
+  online_model_config.provider = provider;
+  online_model_config.tokens = tokens;
+  online_model_config.t_one_ctc = t_one_ctc;
+
+  // Recognizer config
+  SherpaOnnxOnlineRecognizerConfig recognizer_config;
+  memset(&recognizer_config, 0, sizeof(recognizer_config));
+  recognizer_config.decoding_method = "greedy_search";
+  recognizer_config.model_config = online_model_config;
+
+  const SherpaOnnxOnlineRecognizer *recognizer =
+      SherpaOnnxCreateOnlineRecognizer(&recognizer_config);
+
+  if (recognizer == NULL) {
+    fprintf(stderr, "Please check your config!\n");
+    SherpaOnnxFreeWave(wave);
+    return -1;
+  }
+
+  const SherpaOnnxOnlineStream *stream =
+      SherpaOnnxCreateOnlineStream(recognizer);
+
+  const SherpaOnnxDisplay *display = SherpaOnnxCreateDisplay(50);
+  int32_t segment_id = 0;
+
+// simulate streaming. You can choose an arbitrary N
+#define N 3200
+
+  fprintf(stderr, "sample rate: %d, num samples: %d, duration: %.2f s\n",
+          wave->sample_rate, wave->num_samples,
+          (float)wave->num_samples / wave->sample_rate);
+
+  float left_paddings[2400] = {0};  // 0.3 seconds at 8 kHz sample rate
+  SherpaOnnxOnlineStreamAcceptWaveform(stream, wave->sample_rate, left_paddings,
+                                       2400);
+
+  int32_t k = 0;
+  while (k < wave->num_samples) {
+    int32_t start = k;
+    int32_t end =
+        (start + N > wave->num_samples) ? wave->num_samples : (start + N);
+    k += N;
+
+    SherpaOnnxOnlineStreamAcceptWaveform(stream, wave->sample_rate,
+                                         wave->samples + start, end - start);
+    while (SherpaOnnxIsOnlineStreamReady(recognizer, stream)) {
+      SherpaOnnxDecodeOnlineStream(recognizer, stream);
+    }
+
+    const SherpaOnnxOnlineRecognizerResult *r =
+        SherpaOnnxGetOnlineStreamResult(recognizer, stream);
+
+    if (strlen(r->text)) {
+      SherpaOnnxPrint(display, segment_id, r->text);
+    }
+
+    if (SherpaOnnxOnlineStreamIsEndpoint(recognizer, stream)) {
+      if (strlen(r->text)) {
+        ++segment_id;
+      }
+      SherpaOnnxOnlineStreamReset(recognizer, stream);
+    }
+
+    SherpaOnnxDestroyOnlineRecognizerResult(r);
+  }
+
+  // add some tail padding
+  float tail_paddings[4800] = {0};  // 0.6 seconds at 8 kHz sample rate
+  SherpaOnnxOnlineStreamAcceptWaveform(stream, wave->sample_rate, tail_paddings,
+                                       4800);
+
+  SherpaOnnxOnlineStreamInputFinished(stream);
+  while (SherpaOnnxIsOnlineStreamReady(recognizer, stream)) {
+    SherpaOnnxDecodeOnlineStream(recognizer, stream);
+  }
+
+  SherpaOnnxFreeWave(wave);
+
+  const SherpaOnnxOnlineRecognizerResult *r =
+      SherpaOnnxGetOnlineStreamResult(recognizer, stream);
+
+  if (strlen(r->text)) {
+    SherpaOnnxPrint(display, segment_id, r->text);
+  }
+
+  SherpaOnnxDestroyOnlineRecognizerResult(r);
+
+  SherpaOnnxDestroyDisplay(display);
+  SherpaOnnxDestroyOnlineStream(stream);
+  SherpaOnnxDestroyOnlineRecognizer(recognizer);
+  fprintf(stderr, "\n");
+
+  return 0;
+}

@@ -15,6 +15,9 @@ target_link_libraries(kws-cxx-api sherpa-onnx-cxx-api)
 add_executable(streaming-zipformer-rtf-cxx-api ./streaming-zipformer-rtf-cxx-api.cc)
 target_link_libraries(streaming-zipformer-rtf-cxx-api sherpa-onnx-cxx-api)
 
+add_executable(streaming-t-one-ctc-cxx-api   streaming-t-one-ctc-cxx-api.cc)
+target_link_libraries(streaming-t-one-ctc-cxx-api sherpa-onnx-cxx-api)
+
 add_executable(whisper-cxx-api ./whisper-cxx-api.cc)
 target_link_libraries(whisper-cxx-api sherpa-onnx-cxx-api)
 

+// cxx-api-examples/streaming-t-one-ctc-cxx-api.cc
+// Copyright (c)  2025  Xiaomi Corporation
+
+//
+// This file demonstrates how to use streaming T-one
+// with sherpa-onnx's C++ API.
+//
+// clang-format off
+//
+// wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+// tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+// rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+//
+// clang-format on
+
+#include <chrono>  // NOLINT
+#include <iostream>
+#include <string>
+
+#include "sherpa-onnx/c-api/cxx-api.h"
+
+int32_t main() {
+  using namespace sherpa_onnx::cxx;  // NOLINT
+  OnlineRecognizerConfig config;
+
+  // please see
+  config.model_config.t_one_ctc.model =
+      "sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx";
+
+  config.model_config.tokens =
+      "sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt";
+
+  config.model_config.num_threads = 1;
+
+  std::cout << "Loading model\n";
+  OnlineRecognizer recognizer = OnlineRecognizer::Create(config);
+  if (!recognizer.Get()) {
+    std::cerr << "Please check your config\n";
+    return -1;
+  }
+  std::cout << "Loading model done\n";
+
+  std::string wave_filename =
+      "sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav";
+
+  Wave wave = ReadWave(wave_filename);
+  if (wave.samples.empty()) {
+    std::cerr << "Failed to read: '" << wave_filename << "'\n";
+    return -1;
+  }
+
+  std::cout << "Start recognition\n";
+  const auto begin = std::chrono::steady_clock::now();
+
+  OnlineStream stream = recognizer.CreateStream();
+  std::vector<float> left_padding(2400);  // 0.3 seconds at 8kHz
+  std::vector<float> tail_padding(4800);  // 0.6 seconds at 8kHz
+
+  stream.AcceptWaveform(wave.sample_rate, left_padding.data(),
+                        left_padding.size());
+  stream.AcceptWaveform(wave.sample_rate, wave.samples.data(),
+                        wave.samples.size());
+  stream.AcceptWaveform(wave.sample_rate, tail_padding.data(),
+                        tail_padding.size());
+  stream.InputFinished();
+
+  while (recognizer.IsReady(&stream)) {
+    recognizer.Decode(&stream);
+  }
+
+  OnlineRecognizerResult result = recognizer.GetResult(&stream);
+
+  const auto end = std::chrono::steady_clock::now();
+  const float elapsed_seconds =
+      std::chrono::duration_cast<std::chrono::milliseconds>(end - begin)
+          .count() /
+      1000.;
+  float duration = wave.samples.size() / static_cast<float>(wave.sample_rate);
+  float rtf = elapsed_seconds / duration;
+
+  std::cout << "text: " << result.text << "\n";
+  printf("Number of threads: %d\n", config.model_config.num_threads);
+  printf("Duration: %.3fs\n", duration);
+  printf("Elapsed seconds: %.3fs\n", elapsed_seconds);
+  printf("(Real time factor) RTF = %.3f / %.3f = %.3f\n", elapsed_seconds,
+         duration, rtf);
+
+  return 0;
+}

+// Copyright (c)  2024  Xiaomi Corporation
+import 'dart:io';
+import 'dart:typed_data';
+
+import 'package:args/args.dart';
+import 'package:sherpa_onnx/sherpa_onnx.dart' as sherpa_onnx;
+
+import './init.dart';
+
+void main(List<String> arguments) async {
+  await initSherpaOnnx();
+
+  final parser = ArgParser()
+    ..addOption('model', help: 'Path to the model')
+    ..addOption('tokens', help: 'Path to tokens.txt')
+    ..addOption('input-wav', help: 'Path to input.wav to transcribe');
+
+  final res = parser.parse(arguments);
+  if (res['model'] == null ||
+      res['tokens'] == null ||
+      res['input-wav'] == null) {
+    print(parser.usage);
+    exit(1);
+  }
+
+  final model = res['model'] as String;
+  final tokens = res['tokens'] as String;
+  final inputWav = res['input-wav'] as String;
+
+  final ctc = sherpa_onnx.OnlineToneCtcModelConfig(
+    model: model,
+  );
+
+  final modelConfig = sherpa_onnx.OnlineModelConfig(
+    toneCtc: ctc,
+    tokens: tokens,
+    debug: true,
+    numThreads: 1,
+  );
+  final config = sherpa_onnx.OnlineRecognizerConfig(model: modelConfig);
+  final recognizer = sherpa_onnx.OnlineRecognizer(config);
+
+  final waveData = sherpa_onnx.readWave(inputWav);
+  final stream = recognizer.createStream();
+
+  // 0.3 seconds, assume sampleRate is 8kHz
+  final leftPaddings = Float32List(2400);
+  stream.acceptWaveform(
+    samples: leftPaddings,
+    sampleRate: waveData.sampleRate,
+  );
+
+  // simulate streaming. You can choose an arbitrary chunk size.
+  // chunkSize of a single sample is also ok, i.e, chunkSize = 1
+  final chunkSize = 1600; // 0.1 second for 16kHz
+  final numChunks = waveData.samples.length ~/ chunkSize;
+
+  var last = '';
+  for (int i = 0; i != numChunks; ++i) {
+    int start = i * chunkSize;
+    stream.acceptWaveform(
+      samples:
+          Float32List.sublistView(waveData.samples, start, start + chunkSize),
+      sampleRate: waveData.sampleRate,
+    );
+    while (recognizer.isReady(stream)) {
+      recognizer.decode(stream);
+    }
+    final result = recognizer.getResult(stream);
+    if (result.text != last && result.text != '') {
+      last = result.text;
+      print(last);
+    }
+  }
+
+  // 0.6 seconds, assume sampleRate is 8kHz
+  final tailPaddings = Float32List(4800);
+  stream.acceptWaveform(
+    samples: tailPaddings,
+    sampleRate: waveData.sampleRate,
+  );
+
+  while (recognizer.isReady(stream)) {
+    recognizer.decode(stream);
+  }
+
+  final result = recognizer.getResult(stream);
+
+  if (result.text != '') {
+    print(result.text);
+  }
+
+  stream.free();
+  recognizer.free();
+}

+#!/usr/bin/env bash
+
+set -ex
+
+dart pub get
+
+if [ ! -f ./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+fi
+
+dart run \
+  ./bin/t-one-ctc.dart \
+  --model ./sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx \
+  --tokens ./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt \
+  --input-wav ./sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav

@@ -38,6 +38,9 @@ class OnlineDecodeFiles
     [Option("zipformer2-ctc", Required = false, HelpText = "Path to zipformer2 CTC onnx model")]
     public string Zipformer2Ctc { get; set; } = string.Empty;
 
+    [Option("t-one-ctc", Required = false, HelpText = "Path to T-one CTC onnx model")]
+    public string ToneCtc { get; set; } = string.Empty;
+
     [Option("num-threads", Required = false, Default = 1, HelpText = "Number of threads for computation")]
     public int NumThreads { get; set; } = 1;
 
@@ -173,6 +176,7 @@ to download pre-trained streaming models.
     config.ModelConfig.Paraformer.Decoder = options.ParaformerDecoder;
 
     config.ModelConfig.Zipformer2Ctc.Model = options.Zipformer2Ctc;
+    config.ModelConfig.ToneCtc.Model = options.ToneCtc;
 
     config.ModelConfig.Tokens = options.Tokens;
     config.ModelConfig.Provider = options.Provider;
@@ -203,10 +207,15 @@ to download pre-trained streaming models.
       var s = recognizer.CreateStream();
 
       var waveReader = new WaveReader(files[i]);
+
+      var leftPadding = new float[(int)(waveReader.SampleRate * 0.3)];
+      s.AcceptWaveform(waveReader.SampleRate, leftPadding);
+
       s.AcceptWaveform(waveReader.SampleRate, waveReader.Samples);
 
-      var tailPadding = new float[(int)(waveReader.SampleRate * 0.3)];
+      var tailPadding = new float[(int)(waveReader.SampleRate * 0.6)];
       s.AcceptWaveform(waveReader.SampleRate, tailPadding);
+
       s.InputFinished();
 
       streams.Add(s);

+#!/usr/bin/env bash
+
+set -ex
+
+if [ ! -f ./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+fi
+
+dotnet run -c Release \
+  --tokens ./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt \
+  --t-one-ctc ./sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx \
+  --files ./sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav

@@ -107,12 +107,34 @@ class OnlineNemoCtcModelConfig {
   final String model;
 }
 
+class OnlineToneCtcModelConfig {
+  const OnlineToneCtcModelConfig({this.model = ''});
+
+  factory OnlineToneCtcModelConfig.fromJson(Map<String, dynamic> json) {
+    return OnlineToneCtcModelConfig(
+      model: json['model'] as String? ?? '',
+    );
+  }
+
+  @override
+  String toString() {
+    return 'OnlineToneCtcModelConfig(model: $model)';
+  }
+
+  Map<String, dynamic> toJson() => {
+        'model': model,
+      };
+
+  final String model;
+}
+
 class OnlineModelConfig {
   const OnlineModelConfig({
     this.transducer = const OnlineTransducerModelConfig(),
     this.paraformer = const OnlineParaformerModelConfig(),
     this.zipformer2Ctc = const OnlineZipformer2CtcModelConfig(),
     this.nemoCtc = const OnlineNemoCtcModelConfig(),
+    this.toneCtc = const OnlineToneCtcModelConfig(),
     required this.tokens,
     this.numThreads = 1,
     this.provider = 'cpu',
@@ -132,6 +154,8 @@ class OnlineModelConfig {
           json['zipformer2Ctc'] as Map<String, dynamic>? ?? const {}),
       nemoCtc: OnlineNemoCtcModelConfig.fromJson(
           json['nemoCtc'] as Map<String, dynamic>? ?? const {}),
+      toneCtc: OnlineToneCtcModelConfig.fromJson(
+          json['toneCtc'] as Map<String, dynamic>? ?? const {}),
       tokens: json['tokens'] as String,
       numThreads: json['numThreads'] as int? ?? 1,
       provider: json['provider'] as String? ?? 'cpu',
@@ -144,7 +168,7 @@ class OnlineModelConfig {
 
   @override
   String toString() {
-    return 'OnlineModelConfig(transducer: $transducer, paraformer: $paraformer, zipformer2Ctc: $zipformer2Ctc, nemoCtc: $nemoCtc, tokens: $tokens, numThreads: $numThreads, provider: $provider, debug: $debug, modelType: $modelType, modelingUnit: $modelingUnit, bpeVocab: $bpeVocab)';
+    return 'OnlineModelConfig(transducer: $transducer, paraformer: $paraformer, zipformer2Ctc: $zipformer2Ctc, nemoCtc: $nemoCtc, toneCtc: $toneCtc, tokens: $tokens, numThreads: $numThreads, provider: $provider, debug: $debug, modelType: $modelType, modelingUnit: $modelingUnit, bpeVocab: $bpeVocab)';
   }
 
   Map<String, dynamic> toJson() => {
@@ -152,6 +176,7 @@ class OnlineModelConfig {
         'paraformer': paraformer.toJson(),
         'zipformer2Ctc': zipformer2Ctc.toJson(),
         'nemoCtc': nemoCtc.toJson(),
+        'toneCtc': toneCtc.toJson(),
         'tokens': tokens,
         'numThreads': numThreads,
         'provider': provider,
@@ -165,6 +190,7 @@ class OnlineModelConfig {
   final OnlineParaformerModelConfig paraformer;
   final OnlineZipformer2CtcModelConfig zipformer2Ctc;
   final OnlineNemoCtcModelConfig nemoCtc;
+  final OnlineToneCtcModelConfig toneCtc;
 
   final String tokens;
 
@@ -362,6 +388,9 @@ class OnlineRecognizer {
     // nemoCtc
     c.ref.model.nemoCtc.model = config.model.nemoCtc.model.toNativeUtf8();
 
+    // toneCtc
+    c.ref.model.toneCtc.model = config.model.toneCtc.model.toNativeUtf8();
+
     c.ref.model.tokens = config.model.tokens.toNativeUtf8();
     c.ref.model.numThreads = config.model.numThreads;
     c.ref.model.provider = config.model.provider.toNativeUtf8();
@@ -415,6 +444,7 @@ class OnlineRecognizer {
     calloc.free(c.ref.model.modelType);
     calloc.free(c.ref.model.provider);
     calloc.free(c.ref.model.tokens);
+    calloc.free(c.ref.model.toneCtc.model);
     calloc.free(c.ref.model.nemoCtc.model);
     calloc.free(c.ref.model.zipformer2Ctc.model);
     calloc.free(c.ref.model.paraformer.encoder);

@@ -403,6 +403,10 @@ final class SherpaOnnxOnlineNemoCtcModelConfig extends Struct {
   external Pointer<Utf8> model;
 }
 
+final class SherpaOnnxOnlineToneCtcModelConfig extends Struct {
+  external Pointer<Utf8> model;
+}
+
 final class SherpaOnnxOnlineModelConfig extends Struct {
   external SherpaOnnxOnlineTransducerModelConfig transducer;
   external SherpaOnnxOnlineParaformerModelConfig paraformer;
@@ -430,6 +434,8 @@ final class SherpaOnnxOnlineModelConfig extends Struct {
   external int tokensBufSize;
 
   external SherpaOnnxOnlineNemoCtcModelConfig nemoCtc;
+
+  external SherpaOnnxOnlineToneCtcModelConfig toneCtc;
 }
 
 final class SherpaOnnxOnlineCtcFstDecoderConfig extends Struct {

@@ -27,6 +27,7 @@ func main() {
 	flag.StringVar(&config.ModelConfig.Paraformer.Encoder, "paraformer-encoder", "", "Path to the paraformer encoder model")
 	flag.StringVar(&config.ModelConfig.Paraformer.Decoder, "paraformer-decoder", "", "Path to the paraformer decoder model")
 	flag.StringVar(&config.ModelConfig.Zipformer2Ctc.Model, "zipformer2-ctc", "", "Path to the zipformer2 CTC model")
+	flag.StringVar(&config.ModelConfig.ToneCtc.Model, "t-one-ctc", "", "Path to the T-one CTC model")
 	flag.StringVar(&config.ModelConfig.Tokens, "tokens", "", "Path to the tokens file")
 	flag.IntVar(&config.ModelConfig.NumThreads, "num-threads", 1, "Number of threads for computing")
 	flag.IntVar(&config.ModelConfig.Debug, "debug", 0, "Whether to show debug message")
@@ -59,9 +60,12 @@ func main() {
 	stream := sherpa.NewOnlineStream(recognizer)
 	defer sherpa.DeleteOnlineStream(stream)
 
+	leftPadding := make([]float32, int(float32(sampleRate)*0.3))
+	stream.AcceptWaveform(sampleRate, leftPadding)
+
 	stream.AcceptWaveform(sampleRate, samples)
 
-	tailPadding := make([]float32, int(float32(sampleRate)*0.3))
+	tailPadding := make([]float32, int(float32(sampleRate)*0.6))
 	stream.AcceptWaveform(sampleRate, tailPadding)
 
 	for recognizer.IsReady(stream) {

+#!/usr/bin/env bash
+
+set -ex
+
+
+if [ ! -f ./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+fi
+
+go mod tidy
+go build
+
+./streaming-decode-files \
+  --t-one-ctc ./sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx \
+  --tokens ./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt \
+  ./sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav

@@ -26,8 +26,9 @@ export { Samples,
 
 export { OnlineStream,
   OnlineNemoCtcModelConfig,
-  OnlineTransducerModelConfig,
   OnlineParaformerModelConfig,
+  OnlineToneCtcModelConfig,
+  OnlineTransducerModelConfig,
   OnlineZipformer2CtcModelConfig,
   OnlineModelConfig,
   OnlineCtcFstDecoderConfig,

@@ -89,6 +89,22 @@ static SherpaOnnxOnlineNemoCtcModelConfig GetOnlineNemoCtcModelConfig(
   return c;
 }
 
+static SherpaOnnxOnlineToneCtcModelConfig GetOnlineToneCtcModelConfig(
+    Napi::Object obj) {
+  SherpaOnnxOnlineToneCtcModelConfig c;
+  memset(&c, 0, sizeof(c));
+
+  if (!obj.Has("toneCtc") || !obj.Get("toneCtc").IsObject()) {
+    return c;
+  }
+
+  Napi::Object o = obj.Get("toneCtc").As<Napi::Object>();
+
+  SHERPA_ONNX_ASSIGN_ATTR_STR(model, model);
+
+  return c;
+}
+
 static SherpaOnnxOnlineParaformerModelConfig GetOnlineParaformerModelConfig(
     Napi::Object obj) {
   SherpaOnnxOnlineParaformerModelConfig c;
@@ -120,6 +136,7 @@ SherpaOnnxOnlineModelConfig GetOnlineModelConfig(Napi::Object obj) {
   c.paraformer = GetOnlineParaformerModelConfig(o);
   c.zipformer2_ctc = GetOnlineZipformer2CtcModelConfig(o);
   c.nemo_ctc = GetOnlineNemoCtcModelConfig(o);
+  c.t_one_ctc = GetOnlineToneCtcModelConfig(o);
 
   SHERPA_ONNX_ASSIGN_ATTR_STR(tokens, tokens);
   SHERPA_ONNX_ASSIGN_ATTR_INT32(num_threads, numThreads);
@@ -265,6 +282,7 @@ static Napi::External<SherpaOnnxOnlineRecognizer> CreateOnlineRecognizerWrapper(
   SHERPA_ONNX_DELETE_C_STR(c.model_config.paraformer.encoder);
   SHERPA_ONNX_DELETE_C_STR(c.model_config.paraformer.decoder);
 
+  SHERPA_ONNX_DELETE_C_STR(c.model_config.t_one_ctc.model);
   SHERPA_ONNX_DELETE_C_STR(c.model_config.nemo_ctc.model);
   SHERPA_ONNX_DELETE_C_STR(c.model_config.zipformer2_ctc.model);
   SHERPA_ONNX_DELETE_C_STR(c.model_config.tokens);

@@ -50,11 +50,16 @@ export class OnlineNemoCtcModelConfig {
   public model: string = '';
 }
 
+export class OnlineToneCtcModelConfig {
+  public model: string = '';
+}
+
 export class OnlineModelConfig {
   public transducer: OnlineTransducerModelConfig = new OnlineTransducerModelConfig();
   public paraformer: OnlineParaformerModelConfig = new OnlineParaformerModelConfig();
-  public zipformer2_ctc: OnlineZipformer2CtcModelConfig = new OnlineZipformer2CtcModelConfig();
-  public nemo_ctc: OnlineNemoCtcModelConfig = new OnlineNemoCtcModelConfig();
+  public zipformer2Ctc: OnlineZipformer2CtcModelConfig = new OnlineZipformer2CtcModelConfig();
+  public nemoCtc: OnlineNemoCtcModelConfig = new OnlineNemoCtcModelConfig();
+  public toneCtc: OnlineToneCtcModelConfig = new OnlineToneCtcModelConfig();
   public tokens: string = '';
   public numThreads: number = 1;
   public provider: string = 'cpu';

+// Copyright 2024 Xiaomi Corporation
+
+// This file shows how to use an online T-one CTC model, i.e.,
+// streaming T-one CTC model, to decode files.
+import com.k2fsa.sherpa.onnx.*;
+
+public class StreamingDecodeFileToneCtc {
+  public static void main(String[] args) {
+    String model = "./sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx";
+    String tokens = "./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt";
+    String waveFilename = "./sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav";
+
+    WaveReader reader = new WaveReader(waveFilename);
+
+    OnlineToneCtcModelConfig ctc = OnlineToneCtcModelConfig.builder().setModel(model).build();
+
+    OnlineModelConfig modelConfig =
+        OnlineModelConfig.builder()
+            .setToneCtc(ctc)
+            .setTokens(tokens)
+            .setNumThreads(1)
+            .setDebug(true)
+            .build();
+
+    OnlineRecognizerConfig config =
+        OnlineRecognizerConfig.builder()
+            .setOnlineModelConfig(modelConfig)
+            .setDecodingMethod("greedy_search")
+            .build();
+
+    OnlineRecognizer recognizer = new OnlineRecognizer(config);
+    OnlineStream stream = recognizer.createStream();
+
+    float[] leftPaddings = new float[(int) (0.3 * reader.getSampleRate())];
+    stream.acceptWaveform(leftPaddings, reader.getSampleRate());
+
+    stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
+
+    float[] tailPaddings = new float[(int) (0.6 * reader.getSampleRate())];
+    stream.acceptWaveform(tailPaddings, reader.getSampleRate());
+
+    while (recognizer.isReady(stream)) {
+      recognizer.decode(stream);
+    }
+
+    String text = recognizer.getResult(stream).getText();
+
+    System.out.printf("filename:%s\nresult:%s\n", waveFilename, text);
+
+    stream.release();
+    recognizer.release();
+  }
+}

+#!/usr/bin/env bash
+set -ex
+
+if [[ ! -f ../build/lib/libsherpa-onnx-jni.dylib  && ! -f ../build/lib/libsherpa-onnx-jni.so ]]; then
+  mkdir -p ../build
+  pushd ../build
+  cmake \
+    -DSHERPA_ONNX_ENABLE_PYTHON=OFF \
+    -DSHERPA_ONNX_ENABLE_TESTS=OFF \
+    -DSHERPA_ONNX_ENABLE_CHECK=OFF \
+    -DBUILD_SHARED_LIBS=ON \
+    -DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
+    -DSHERPA_ONNX_ENABLE_JNI=ON \
+    ..
+
+  make -j4
+  ls -lh lib
+  popd
+fi
+
+if [ ! -f ../sherpa-onnx/java-api/build/sherpa-onnx.jar ]; then
+  pushd ../sherpa-onnx/java-api
+  make
+  popd
+fi
+
+if [ ! -f ./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+fi
+
+java \
+  -Djava.library.path=$PWD/../build/lib \
+  -cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
+  StreamingDecodeFileToneCtc.java

@@ -72,6 +72,12 @@ function testSpeakerEmbeddingExtractor() {
 
 
 function testOnlineAsr() {
+  if [ ! -f ./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt ]; then
+    curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+    tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+    rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  fi
+
   if [ ! -f ./sherpa-onnx-streaming-zipformer-en-2023-02-21/tokens.txt ]; then
     git lfs install
     GIT_CLONE_PROTECTION_ACTIVE=false git clone https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-en-2023-02-21

@@ -5,6 +5,7 @@ fun main() {
   testOnlineAsr("zipformer2-ctc")
   testOnlineAsr("ctc-hlg")
   testOnlineAsr("nemo-ctc")
+  testOnlineAsr("tone-ctc")
 }
 
 fun testOnlineAsr(type: String) {
@@ -54,6 +55,17 @@ fun testOnlineAsr(type: String) {
             debug = false,
         )
       }
+      "tone-ctc" -> {
+        waveFilename = "./sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav"
+        OnlineModelConfig(
+            toneCtc = OnlineToneCtcModelConfig(
+                model = "./sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx",
+            ),
+            tokens = "./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt",
+            numThreads = 1,
+            debug = false,
+        )
+      }
       "ctc-hlg" -> {
         waveFilename = "./sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18/test_wavs/1.wav"
         ctcFstDecoderConfig.graph = "./sherpa-onnx-streaming-zipformer-ctc-small-2024-03-18/HLG.fst"
@@ -95,12 +107,16 @@ fun testOnlineAsr(type: String) {
     val sampleRate: Int = objArray[1] as Int
 
     val stream = recognizer.createStream()
+
+    val leftPaddings = FloatArray((sampleRate * 0.3).toInt()) // 0.3 seconds
+    stream.acceptWaveform(leftPaddings, sampleRate = sampleRate)
+
     stream.acceptWaveform(samples, sampleRate = sampleRate)
     while (recognizer.isReady(stream)) {
         recognizer.decode(stream)
     }
 
-    val tailPaddings = FloatArray((sampleRate * 0.5).toInt()) // 0.5 seconds
+    val tailPaddings = FloatArray((sampleRate * 0.6).toInt()) // 0.6 seconds
     stream.acceptWaveform(tailPaddings, sampleRate = sampleRate)
     stream.inputFinished()
     while (recognizer.isReady(stream)) {

@@ -97,6 +97,7 @@ The following tables list the examples in this folder.
 
 |File| Description|
 |---|---|
+|[./test_asr_streaming_t_one_ctc.js](./test_asr_streaming_t_one_ctc.js)| Streaming speech recognition from a file using a T-one CTC model|
 |[./test_asr_streaming_transducer.js](./test_asr_streaming_transducer.js)| Streaming speech recognition from a file using a Zipformer transducer model|
 |[./test_asr_streaming_transducer_with_hr.js](./test_asr_streaming_transducer_with_hr.js)| Streaming speech recognition from a file using a Zipformer transducer model with homophone replacer|
 |[./test_asr_streaming_ctc.js](./test_asr_streaming_ctc.js)| Streaming speech recognition from a file using a Zipformer CTC model with greedy search|
@@ -230,6 +231,16 @@ curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/hr-files/lex
 node ./test_asr_streaming_transducer_with_hr.js
 ```
 
+### Streaming speech recognition with T-one CTC
+
+```bash
+wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+
+node ./test_asr_streaming_t_one_ctc.js
+```
+
 ### Streaming speech recognition with Zipformer transducer
 
 ```bash

+// Copyright (c)  2025  Xiaomi Corporation
+const sherpa_onnx = require('sherpa-onnx-node');
+
+// Please download test files from
+// https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+const config = {
+  'modelConfig': {
+    'toneCtc': {
+      'model': './sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx',
+    },
+    'tokens': './sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt',
+    'numThreads': 2,
+    'provider': 'cpu',
+    'debug': 1,
+  }
+};
+
+const waveFilename = './sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav';
+
+const recognizer = new sherpa_onnx.OnlineRecognizer(config);
+console.log('Started')
+let start = Date.now();
+const stream = recognizer.createStream();
+const wave = sherpa_onnx.readWave(waveFilename);
+
+const leftPadding = new Float32Array(wave.sampleRate * 0.3);
+stream.acceptWaveform({samples: leftPadding, sampleRate: wave.sampleRate});
+
+stream.acceptWaveform({sampleRate: wave.sampleRate, samples: wave.samples});
+
+const tailPadding = new Float32Array(wave.sampleRate * 0.6);
+stream.acceptWaveform({samples: tailPadding, sampleRate: wave.sampleRate});
+
+while (recognizer.isReady(stream)) {
+  recognizer.decode(stream);
+}
+result = recognizer.getResult(stream)
+let stop = Date.now();
+console.log('Done')
+
+const elapsed_seconds = (stop - start) / 1000;
+const duration = wave.samples.length / wave.sampleRate;
+const real_time_factor = elapsed_seconds / duration;
+console.log('Wave duration', duration.toFixed(3), 'seconds')
+console.log('Elapsed', elapsed_seconds.toFixed(3), 'seconds')
+console.log(
+    `RTF = ${elapsed_seconds.toFixed(3)}/${duration.toFixed(3)} =`,
+    real_time_factor.toFixed(3))
+console.log(waveFilename)
+console.log('result\n', result)

@@ -393,6 +393,18 @@ rm sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
 node ./test-online-paraformer-microphone-mic.js
 ```
 
+## ./test-online-t-one-ctc.js
+[./test-online-t-one-ctc.js](./test-online-t-one-ctc.js) demonstrates
+how to decode a file using a streaming T-one model.
+
+You can use the following command to run it:
+
+```bash
+wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+node ./test-online-t-one-ctc.js
+```
 
 ## ./test-online-paraformer.js
 [./test-online-paraformer.js](./test-online-paraformer.js) demonstrates

+// Copyright (c)  2023  Xiaomi Corporation (authors: Fangjun Kuang)
+//
+const fs = require('fs');
+const {Readable} = require('stream');
+const wav = require('wav');
+
+const sherpa_onnx = require('sherpa-onnx');
+
+function createOnlineRecognizer() {
+  let toneCtc = {
+    model: './sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx',
+  };
+
+  let onlineModelConfig = {
+    toneCtc: toneCtc,
+    tokens: './sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt',
+    numThreads: 1,
+    provider: 'cpu',
+    debug: 1,
+  };
+
+
+  let recognizerConfig = {
+    modelConfig: onlineModelConfig,
+    decodingMethod: 'greedy_search',
+    maxActivePaths: 4,
+    enableEndpoint: 1,
+    rule1MinTrailingSilence: 2.4,
+    rule2MinTrailingSilence: 1.2,
+    rule3MinUtteranceLength: 20,
+  };
+
+  return sherpa_onnx.createOnlineRecognizer(recognizerConfig);
+}
+
+const recognizer = createOnlineRecognizer();
+const stream = recognizer.createStream();
+
+const waveFilename = './sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav';
+const wave = sherpa_onnx.readWave(waveFilename);
+
+const leftPadding = new Float32Array(wave.sampleRate * 0.3);
+const tailPadding = new Float32Array(wave.sampleRate * 0.6);
+
+stream.acceptWaveform(wave.sampleRate, leftPadding);
+stream.acceptWaveform(wave.sampleRate, wave.samples);
+stream.acceptWaveform(wave.sampleRate, tailPadding);
+
+while (recognizer.isReady(stream)) {
+  recognizer.decode(stream);
+}
+const text = recognizer.getResult(stream).text;
+console.log(text);
+
+stream.free();
+recognizer.free();

@@ -4,3 +4,4 @@ paraformer
 zipformer_ctc
 zipformer_ctc_hlg
 nemo_transducer
+t_one_ctc

+#!/usr/bin/env bash
+
+set -ex
+
+SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
+SHERPA_ONNX_DIR=$(cd $SCRIPT_DIR/../.. && pwd)
+
+echo "SHERPA_ONNX_DIR: $SHERPA_ONNX_DIR"
+
+if [[ ! -f ../../build/install/lib/libsherpa-onnx-c-api.dylib  && ! -f ../../build/install/lib/libsherpa-onnx-c-api.so && ! -f ../../build/install/lib/sherpa-onnx-c-api.dll ]]; then
+  mkdir -p ../../build
+  pushd ../../build
+  cmake \
+    -DCMAKE_INSTALL_PREFIX=./install \
+    -DSHERPA_ONNX_ENABLE_PYTHON=OFF \
+    -DSHERPA_ONNX_ENABLE_TESTS=OFF \
+    -DSHERPA_ONNX_ENABLE_CHECK=OFF \
+    -DBUILD_SHARED_LIBS=ON \
+    -DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
+    ..
+
+  cmake --build . --target install --config Release
+  ls -lh lib
+  popd
+fi
+
+if [ ! -f ./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+fi
+
+fpc \
+  -dSHERPA_ONNX_USE_SHARED_LIBS \
+  -Fu$SHERPA_ONNX_DIR/sherpa-onnx/pascal-api \
+  -Fl$SHERPA_ONNX_DIR/build/install/lib \
+  ./t_one_ctc.pas
+
+export LD_LIBRARY_PATH=$SHERPA_ONNX_DIR/build/install/lib:$LD_LIBRARY_PATH
+export DYLD_LIBRARY_PATH=$SHERPA_ONNX_DIR/build/install/lib:$DYLD_LIBRARY_PATH
+
+./t_one_ctc

+{ Copyright (c)  2025  Xiaomi Corporation }
+
+{
+This file shows how to use a streaming T-one CTC model
+to decode files.
+
+You can download the model files from
+https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+}
+
+program t_one_ctc;
+
+{$mode objfpc}
+
+uses
+  sherpa_onnx,
+  DateUtils,
+  SysUtils;
+
+var
+  Config: TSherpaOnnxOnlineRecognizerConfig;
+  Recognizer: TSherpaOnnxOnlineRecognizer;
+  Stream: TSherpaOnnxOnlineStream;
+  RecognitionResult: TSherpaOnnxOnlineRecognizerResult;
+  Wave: TSherpaOnnxWave;
+  WaveFilename: AnsiString;
+  LeftPaddings: array of Single;
+  TailPaddings: array of Single;
+
+  Start: TDateTime;
+  Stop: TDateTime;
+
+  Elapsed: Single;
+  Duration: Single;
+  RealTimeFactor: Single;
+begin
+  Initialize(Config);
+
+  {Please visit https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+  to download model files used in this file.}
+  Config.ModelConfig.ToneCtc.Model := './sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx';
+  Config.ModelConfig.Tokens := './sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt';
+  Config.ModelConfig.Provider := 'cpu';
+  Config.ModelConfig.NumThreads := 1;
+  Config.ModelConfig.Debug := False;
+
+  WaveFilename := './sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav';
+
+  Wave := SherpaOnnxReadWave(WaveFilename);
+
+  Recognizer := TSherpaOnnxOnlineRecognizer.Create(Config);
+
+  Start := Now;
+
+  Stream := Recognizer.CreateStream();
+
+  SetLength(LeftPaddings, Round(Wave.SampleRate * 0.3)); {0.3 seconds of padding}
+  Stream.AcceptWaveform(LeftPaddings, Wave.SampleRate);
+
+  Stream.AcceptWaveform(Wave.Samples, Wave.SampleRate);
+
+  SetLength(TailPaddings, Round(Wave.SampleRate * 0.6)); {0.6 seconds of padding}
+  Stream.AcceptWaveform(TailPaddings, Wave.SampleRate);
+
+  Stream.InputFinished();
+
+  while Recognizer.IsReady(Stream) do
+    Recognizer.Decode(Stream);
+
+  RecognitionResult := Recognizer.GetResult(Stream);
+
+  Stop := Now;
+
+  Elapsed := MilliSecondsBetween(Stop, Start) / 1000;
+  Duration := Length(Wave.Samples) / Wave.SampleRate;
+  RealTimeFactor := Elapsed / Duration;
+
+  WriteLn(RecognitionResult.ToString);
+  WriteLn(Format('NumThreads %d', [Config.ModelConfig.NumThreads]));
+  WriteLn(Format('Elapsed %.3f s', [Elapsed]));
+  WriteLn(Format('Wave duration %.3f s', [Duration]));
+  WriteLn(Format('RTF = %.3f/%.3f = %.3f', [Elapsed, Duration, RealTimeFactor]));
+
+  {Free resources to avoid memory leak.
+
+  Note: You don't need to invoke them for this simple script.
+  However, you have to invoke them in your own large/complex project.
+  }
+  FreeAndNil(Stream);
+  FreeAndNil(Recognizer);
+end.

@@ -469,6 +469,21 @@ def get_models():
             popd
             """,
         ),
+        Model(
+            model_name="sherpa-onnx-streaming-t-one-russian-2025-09-08",
+            idx=27,
+            lang="ru",
+            short_name="t_one_ctc_2025_09_08",
+            cmd="""
+            pushd $model_name
+
+            rm -v *.wav
+
+            ls -lh
+
+            popd
+            """,
+        ),
     ]
 
     return models

@@ -25,6 +25,7 @@ namespace SherpaOnnx
             TokensBuf = "";
             TokensBufSize = 0;
             NemoCtc = new OnlineNemoCtcModelConfig();
+            ToneCtc = new OnlineToneCtcModelConfig();
         }
 
         public OnlineTransducerModelConfig Transducer;
@@ -58,6 +59,8 @@ namespace SherpaOnnx
         public int TokensBufSize;
 
         public OnlineNemoCtcModelConfig NemoCtc;
+
+        public OnlineToneCtcModelConfig ToneCtc;
     }
 
 }

+/// Copyright (c)  2025  Xiaomi Corporation (authors: Fangjun Kuang)
+
+using System.Runtime.InteropServices;
+
+namespace SherpaOnnx
+{
+    [StructLayout(LayoutKind.Sequential)]
+    public struct OnlineToneCtcModelConfig
+    {
+        public OnlineToneCtcModelConfig()
+        {
+            Model = "";
+        }
+
+        [MarshalAs(UnmanagedType.LPStr)]
+        public string Model;
+    }
+}

+../../../../go-api-examples/non-streaming-tts/run-kitten-en.sh
\ No newline at end of file

+../../../../go-api-examples/streaming-decode-files/run-t-one-ctc.sh
\ No newline at end of file

@@ -81,6 +81,10 @@ type OnlineNemoCtcModelConfig struct {
 	Model string // Path to the onnx model
 }
 
+type OnlineToneCtcModelConfig struct {
+	Model string // Path to the onnx model
+}
+
 // Configuration for online/streaming models
 //
 // Please refer to
@@ -92,6 +96,7 @@ type OnlineModelConfig struct {
 	Paraformer    OnlineParaformerModelConfig
 	Zipformer2Ctc OnlineZipformer2CtcModelConfig
 	NemoCtc       OnlineNemoCtcModelConfig
+	ToneCtc       OnlineToneCtcModelConfig
 	Tokens        string // Path to tokens.txt
 	NumThreads    int    // Number of threads to use for neural network computation
 	Provider      string // Optional. Valid values are: cpu, cuda, coreml
@@ -205,6 +210,9 @@ func NewOnlineRecognizer(config *OnlineRecognizerConfig) *OnlineRecognizer {
 	c.model_config.nemo_ctc.model = C.CString(config.ModelConfig.NemoCtc.Model)
 	defer C.free(unsafe.Pointer(c.model_config.nemo_ctc.model))
 
+	c.model_config.t_one_ctc.model = C.CString(config.ModelConfig.ToneCtc.Model)
+	defer C.free(unsafe.Pointer(c.model_config.t_one_ctc.model))
+
 	c.model_config.tokens = C.CString(config.ModelConfig.Tokens)
 	defer C.free(unsafe.Pointer(c.model_config.tokens))
 

@@ -100,6 +100,9 @@ static sherpa_onnx::OnlineRecognizerConfig GetOnlineRecognizerConfig(
   recognizer_config.model_config.nemo_ctc.model =
       SHERPA_ONNX_OR(config->model_config.nemo_ctc.model, "");
 
+  recognizer_config.model_config.t_one_ctc.model =
+      SHERPA_ONNX_OR(config->model_config.t_one_ctc.model, "");
+
   recognizer_config.model_config.num_threads =
       SHERPA_ONNX_OR(config->model_config.num_threads, 1);
   recognizer_config.model_config.provider_config.provider =
@@ -691,8 +694,7 @@ const SherpaOnnxOfflineRecognizerResult *SherpaOnnxGetOfflineStreamResult(
 
     if (!result.durations.empty() && result.durations.size() == r->count) {
       r->durations = new float[r->count];
-      std::copy(result.durations.begin(), result.durations.end(),
-                r->durations);
+      std::copy(result.durations.begin(), result.durations.end(), r->durations);
     } else {
       r->durations = nullptr;
     }

@@ -104,6 +104,10 @@ SHERPA_ONNX_API typedef struct SherpaOnnxOnlineNemoCtcModelConfig {
   const char *model;
 } SherpaOnnxOnlineNemoCtcModelConfig;
 
+SHERPA_ONNX_API typedef struct SherpaOnnxOnlineToneCtcModelConfig {
+  const char *model;
+} SherpaOnnxOnlineToneCtcModelConfig;
+
 SHERPA_ONNX_API typedef struct SherpaOnnxOnlineModelConfig {
   SherpaOnnxOnlineTransducerModelConfig transducer;
   SherpaOnnxOnlineParaformerModelConfig paraformer;
@@ -125,6 +129,7 @@ SHERPA_ONNX_API typedef struct SherpaOnnxOnlineModelConfig {
   /// byte size excluding the trailing '\0'
   int32_t tokens_buf_size;
   SherpaOnnxOnlineNemoCtcModelConfig nemo_ctc;
+  SherpaOnnxOnlineToneCtcModelConfig t_one_ctc;
 } SherpaOnnxOnlineModelConfig;
 
 /// It expects 16 kHz 16-bit single channel wave format.

@@ -70,6 +70,7 @@ OnlineRecognizer OnlineRecognizer::Create(
       config.model_config.zipformer2_ctc.model.c_str();
 
   c.model_config.nemo_ctc.model = config.model_config.nemo_ctc.model.c_str();
+  c.model_config.t_one_ctc.model = config.model_config.t_one_ctc.model.c_str();
 
   c.model_config.tokens = config.model_config.tokens.c_str();
   c.model_config.num_threads = config.model_config.num_threads;

@@ -36,11 +36,16 @@ struct OnlineNemoCtcModelConfig {
   std::string model;
 };
 
+struct OnlineToneCtcModelConfig {
+  std::string model;
+};
+
 struct OnlineModelConfig {
   OnlineTransducerModelConfig transducer;
   OnlineParaformerModelConfig paraformer;
   OnlineZipformer2CtcModelConfig zipformer2_ctc;
   OnlineNemoCtcModelConfig nemo_ctc;
+  OnlineToneCtcModelConfig t_one_ctc;
   std::string tokens;
   int32_t num_threads = 1;
   std::string provider = "cpu";

@@ -19,6 +19,7 @@ java_files += HomophoneReplacerConfig.java
 java_files += OnlineLMConfig.java
 java_files += OnlineParaformerModelConfig.java
 java_files += OnlineZipformer2CtcModelConfig.java
+java_files += OnlineToneCtcModelConfig.java
 java_files += OnlineNeMoCtcModelConfig.java
 java_files += OnlineTransducerModelConfig.java
 java_files += OnlineModelConfig.java

@@ -237,6 +237,7 @@ public class LibraryUtils {
         dir.deleteOnExit(); // schedule the directory itself
     }
 
+    static boolean isAndroid() {
         String vmName = System.getProperty("java.vm.name", "").toLowerCase(Locale.ROOT);
         String specVendor = System.getProperty("java.specification.vendor", "");
         return vmName.contains("dalvik") || vmName.contains("art") ||

@@ -8,6 +8,7 @@ public class OnlineModelConfig {
     private final OnlineParaformerModelConfig paraformer;
     private final OnlineZipformer2CtcModelConfig zipformer2Ctc;
     private final OnlineNeMoCtcModelConfig neMoCtc;
+    private final OnlineToneCtcModelConfig toneCtc;
     private final String tokens;
     private final int numThreads;
     private final boolean debug;
@@ -21,6 +22,7 @@ public class OnlineModelConfig {
         this.paraformer = builder.paraformer;
         this.zipformer2Ctc = builder.zipformer2Ctc;
         this.neMoCtc = builder.neMoCtc;
+        this.toneCtc = builder.toneCtc;
         this.tokens = builder.tokens;
         this.numThreads = builder.numThreads;
         this.debug = builder.debug;
@@ -50,6 +52,10 @@ public class OnlineModelConfig {
         return neMoCtc;
     }
 
+    public OnlineToneCtcModelConfig getToneCtc() {
+        return toneCtc;
+    }
+
     public String getTokens() {
         return tokens;
     }
@@ -83,6 +89,7 @@ public class OnlineModelConfig {
         private OnlineTransducerModelConfig transducer = OnlineTransducerModelConfig.builder().build();
         private OnlineZipformer2CtcModelConfig zipformer2Ctc = OnlineZipformer2CtcModelConfig.builder().build();
         private OnlineNeMoCtcModelConfig neMoCtc = OnlineNeMoCtcModelConfig.builder().build();
+        private OnlineToneCtcModelConfig toneCtc = OnlineToneCtcModelConfig.builder().build();
         private String tokens = "";
         private int numThreads = 1;
         private boolean debug = true;
@@ -115,6 +122,11 @@ public class OnlineModelConfig {
             return this;
         }
 
+        public Builder setToneCtc(OnlineToneCtcModelConfig toneCtc) {
+            this.toneCtc = toneCtc;
+            return this;
+        }
+
         public Builder setTokens(String tokens) {
             this.tokens = tokens;
             return this;

@@ -28,5 +28,4 @@ public class OnlineNeMoCtcModelConfig {
             return this;
         }
     }
-
-}
+}
\ No newline at end of file

+package com.k2fsa.sherpa.onnx;
+
+public class OnlineToneCtcModelConfig {
+    private final String model;
+
+    private OnlineToneCtcModelConfig(Builder builder) {
+        this.model = builder.model;
+    }
+
+    public static Builder builder() {
+        return new Builder();
+    }
+
+    public String getModel() {
+        return model;
+    }
+
+    public static class Builder {
+        private String model = "";
+
+        public OnlineToneCtcModelConfig build() {
+            return new OnlineToneCtcModelConfig(this);
+        }
+
+        public Builder setModel(String model) {
+            this.model = model;
+            return this;
+        }
+    }
+}

@@ -82,6 +82,18 @@ OnlineModelConfig GetOnlineModelConfig(JNIEnv *env, jclass model_config_cls,
   ans.nemo_ctc.model = p;
   env->ReleaseStringUTFChars(s, p);
 
+  // streaming T-one CTC
+  fid = env->GetFieldID(model_config_cls, "toneCtc",
+                        "Lcom/k2fsa/sherpa/onnx/OnlineToneCtcModelConfig;");
+  jobject t_one_ctc_config = env->GetObjectField(model_config, fid);
+  jclass t_one_ctc_config_cls = env->GetObjectClass(t_one_ctc_config);
+
+  fid = env->GetFieldID(t_one_ctc_config_cls, "model", "Ljava/lang/String;");
+  s = (jstring)env->GetObjectField(t_one_ctc_config, fid);
+  p = env->GetStringUTFChars(s, nullptr);
+  ans.t_one_ctc.model = p;
+  env->ReleaseStringUTFChars(s, p);
+
   fid = env->GetFieldID(model_config_cls, "tokens", "Ljava/lang/String;");
   s = (jstring)env->GetObjectField(model_config, fid);
   p = env->GetStringUTFChars(s, nullptr);

@@ -33,11 +33,16 @@ data class OnlineNeMoCtcModelConfig(
     var model: String = "",
 )
 
+data class OnlineToneCtcModelConfig(
+    var model: String = "",
+)
+
 data class OnlineModelConfig(
     var transducer: OnlineTransducerModelConfig = OnlineTransducerModelConfig(),
     var paraformer: OnlineParaformerModelConfig = OnlineParaformerModelConfig(),
     var zipformer2Ctc: OnlineZipformer2CtcModelConfig = OnlineZipformer2CtcModelConfig(),
     var neMoCtc: OnlineNeMoCtcModelConfig = OnlineNeMoCtcModelConfig(),
+    var toneCtc: OnlineToneCtcModelConfig = OnlineToneCtcModelConfig(),
     var tokens: String = "",
     var numThreads: Int = 1,
     var debug: Boolean = false,
@@ -518,6 +523,16 @@ fun getModelConfig(type: Int): OnlineModelConfig? {
             )
         }
 
+        27 -> {
+            val modelDir = "sherpa-onnx-streaming-t-one-russian-2025-09-08"
+            return OnlineModelConfig(
+                toneCtc = OnlineToneCtcModelConfig(
+                    model = "$modelDir/model.onnx",
+                ),
+                tokens = "$modelDir/tokens.txt",
+            )
+        }
+
         1000 -> {
             val modelDir = "sherpa-onnx-rk3588-streaming-zipformer-bilingual-zh-en-2023-02-20"
             return OnlineModelConfig(

@@ -182,6 +182,11 @@ type
     function ToString: AnsiString;
   end;
 
+  TSherpaOnnxOnlineToneCtcModelConfig = record
+    Model: AnsiString;
+    function ToString: AnsiString;
+  end;
+
   TSherpaOnnxOnlineModelConfig = record
     Transducer: TSherpaOnnxOnlineTransducerModelConfig;
     Paraformer: TSherpaOnnxOnlineParaformerModelConfig;
@@ -196,6 +201,7 @@ type
     TokensBuf: AnsiString;
     TokensBufSize: Integer;
     NemoCtc: TSherpaOnnxOnlineNemoCtcModelConfig;
+    ToneCtc: TSherpaOnnxOnlineToneCtcModelConfig;
     function ToString: AnsiString;
     class operator Initialize({$IFDEF FPC}var{$ELSE}out{$ENDIF} Dest: TSherpaOnnxOnlineModelConfig);
   end;
@@ -714,6 +720,10 @@ type
     Model: PAnsiChar;
   end;
 
+  SherpaOnnxOnlineToneCtcModelConfig = record
+    Model: PAnsiChar;
+  end;
+
   SherpaOnnxOnlineModelConfig= record
     Transducer: SherpaOnnxOnlineTransducerModelConfig;
     Paraformer: SherpaOnnxOnlineParaformerModelConfig;
@@ -728,6 +738,7 @@ type
     TokensBuf: PAnsiChar;
     TokensBufSize: cint32;
     NemoCtc: SherpaOnnxOnlineNemoCtcModelConfig;
+    ToneCtc: SherpaOnnxOnlineToneCtcModelConfig;
   end;
   SherpaOnnxFeatureConfig = record
     SampleRate: cint32;
@@ -1350,6 +1361,12 @@ begin
   [Self.Model]);
 end;
 
+function TSherpaOnnxOnlineToneCtcModelConfig.ToString: AnsiString;
+begin
+  Result := Format('TSherpaOnnxOnlineToneCtcModelConfig(Model := %s)',
+  [Self.Model]);
+end;
+
 function TSherpaOnnxOnlineModelConfig.ToString: AnsiString;
 begin
   Result := Format('TSherpaOnnxOnlineModelConfig(Transducer := %s, ' +
@@ -1362,12 +1379,13 @@ begin
     'ModelType := %s, ' +
     'ModelingUnit := %s, ' +
     'BpeVocab := %s, ' +
-    'NemoCtc := %s)',
+    'NemoCtc := %s, ' +
+    'ToneCtc := %s)',
   [Self.Transducer.ToString, Self.Paraformer.ToString,
    Self.Zipformer2Ctc.ToString, Self.Tokens,
    Self.NumThreads, Self.Provider, Self.Debug.ToString,
    Self.ModelType, Self.ModelingUnit, Self.BpeVocab,
-   Self.NemoCtc.ToString
+   Self.NemoCtc.ToString, Self.ToneCtc.ToString
   ]);
 end;
 
@@ -1467,6 +1485,7 @@ begin
 
   C.ModelConfig.Zipformer2Ctc.Model := PAnsiChar(Config.ModelConfig.Zipformer2Ctc.Model);
   C.ModelConfig.NemoCtc.Model := PAnsiChar(Config.ModelConfig.NemoCtc.Model);
+  C.ModelConfig.ToneCtc.Model := PAnsiChar(Config.ModelConfig.ToneCtc.Model);
 
   C.ModelConfig.Tokens := PAnsiChar(Config.ModelConfig.Tokens);
   C.ModelConfig.NumThreads := Config.ModelConfig.NumThreads;

@@ -22,3 +22,4 @@ zipformer-ctc-asr
 dolphin-ctc-asr
 tts-kitten-en
 compute-speaker-embeddings
+decode-file-t-one-streaming

@@ -76,6 +76,14 @@ func sherpaOnnxOnlineNemoCtcModelConfig(
   )
 }
 
+func sherpaOnnxOnlineToneCtcModelConfig(
+  model: String = ""
+) -> SherpaOnnxOnlineToneCtcModelConfig {
+  return SherpaOnnxOnlineToneCtcModelConfig(
+    model: toCPointer(model)
+  )
+}
+
 /// Return an instance of SherpaOnnxOnlineModelConfig.
 ///
 /// Please refer to
@@ -101,7 +109,8 @@ func sherpaOnnxOnlineModelConfig(
   bpeVocab: String = "",
   tokensBuf: String = "",
   tokensBufSize: Int = 0,
-  nemoCtc: SherpaOnnxOnlineNemoCtcModelConfig = sherpaOnnxOnlineNemoCtcModelConfig()
+  nemoCtc: SherpaOnnxOnlineNemoCtcModelConfig = sherpaOnnxOnlineNemoCtcModelConfig(),
+  toneCtc: SherpaOnnxOnlineToneCtcModelConfig = sherpaOnnxOnlineToneCtcModelConfig()
 ) -> SherpaOnnxOnlineModelConfig {
   return SherpaOnnxOnlineModelConfig(
     transducer: transducer,
@@ -116,7 +125,8 @@ func sherpaOnnxOnlineModelConfig(
     bpe_vocab: toCPointer(bpeVocab),
     tokens_buf: toCPointer(tokensBuf),
     tokens_buf_size: Int32(tokensBufSize),
-    nemo_ctc: nemoCtc
+    nemo_ctc: nemoCtc,
+    t_one_ctc: toneCtc
   )
 }
 

+import AVFoundation
+
+extension AudioBuffer {
+  func array() -> [Float] {
+    return Array(UnsafeBufferPointer(self))
+  }
+}
+
+extension AVAudioPCMBuffer {
+  func array() -> [Float] {
+    return self.audioBufferList.pointee.mBuffers.array()
+  }
+}
+
+func run() {
+  let filePath = "./sherpa-onnx-streaming-t-one-russian-2025-09-08/0.wav"
+  let model =
+    "./sherpa-onnx-streaming-t-one-russian-2025-09-08/model.onnx"
+  let tokens = "./sherpa-onnx-streaming-t-one-russian-2025-09-08/tokens.txt"
+
+  let toneCtcConfig = sherpaOnnxOnlineToneCtcModelConfig(
+    model: model)
+
+  let modelConfig = sherpaOnnxOnlineModelConfig(
+    tokens: tokens,
+    toneCtc: toneCtcConfig
+  )
+
+  let featConfig = sherpaOnnxFeatureConfig(
+    sampleRate: 8000,
+    featureDim: 80
+  )
+  var config = sherpaOnnxOnlineRecognizerConfig(
+    featConfig: featConfig,  // not used
+    modelConfig: modelConfig
+  )
+
+  let recognizer = SherpaOnnxRecognizer(config: &config)
+
+  let fileURL: NSURL = NSURL(fileURLWithPath: filePath)
+  let audioFile = try! AVAudioFile(forReading: fileURL as URL)
+
+  let audioFormat = audioFile.processingFormat
+  assert(audioFormat.sampleRate == 8000)
+  assert(audioFormat.channelCount == 1)
+  assert(audioFormat.commonFormat == AVAudioCommonFormat.pcmFormatFloat32)
+
+  let audioFrameCount = UInt32(audioFile.length)
+  let audioFileBuffer = AVAudioPCMBuffer(pcmFormat: audioFormat, frameCapacity: audioFrameCount)
+
+  try! audioFile.read(into: audioFileBuffer!)
+  let array: [Float]! = audioFileBuffer?.array()
+
+  let leftPadding = [Float](repeating: 0.0, count: 2400)
+  recognizer.acceptWaveform(samples: leftPadding, sampleRate: Int(audioFormat.sampleRate))
+
+  recognizer.acceptWaveform(samples: array, sampleRate: Int(audioFormat.sampleRate))
+
+  let tailPadding = [Float](repeating: 0.0, count: 4800)
+  recognizer.acceptWaveform(samples: tailPadding, sampleRate: Int(audioFormat.sampleRate))
+
+  recognizer.inputFinished()
+  while recognizer.isReady() {
+    recognizer.decode()
+  }
+
+  let result = recognizer.getResult()
+  print("\nresult is:\n\(result.text)")
+  print("\nresult is:\n\(result.timestamps)")
+}
+
+@main
+struct App {
+  static func main() {
+    run()
+  }
+}

+#!/usr/bin/env bash
+
+set -ex
+
+if [ ! -d ../build-swift-macos ]; then
+  echo "Please run ../build-swift-macos.sh first!"
+  exit 1
+fi
+
+if [ ! -d ./sherpa-onnx-streaming-t-one-russian-2025-09-08 ]; then
+  echo "Downloading the pre-trained model for testing."
+
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  tar xvf sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+  rm sherpa-onnx-streaming-t-one-russian-2025-09-08.tar.bz2
+fi
+
+if [ ! -e ./decode-file-t-one-streaming ]; then
+  # Note: We use -lc++ to link against libc++ instead of libstdc++
+  swiftc \
+    -lc++ \
+    -I ../build-swift-macos/install/include \
+    -import-objc-header ./SherpaOnnx-Bridging-Header.h \
+    ./decode-file-t-one-streaming.swift  ./SherpaOnnx.swift \
+    -L ../build-swift-macos/install/lib/ \
+    -l sherpa-onnx \
+    -l onnxruntime \
+    -o decode-file-t-one-streaming
+
+  strip decode-file-t-one-streaming
+else
+  echo "./decode-file-t-one-streaming exists - skip building"
+fi
+
+export DYLD_LIBRARY_PATH=$PWD/../build-swift-macos/install/lib:$DYLD_LIBRARY_PATH
+./decode-file-t-one-streaming

@@ -31,6 +31,10 @@ function freeConfig(config, Module) {
     freeConfig(config.nemoCtc, Module)
   }
 
+  if ('toneCtc' in config) {
+    freeConfig(config.toneCtc, Module)
+  }
+
   if ('whisper' in config) {
     freeConfig(config.whisper, Module)
   }
@@ -173,6 +177,22 @@ function initSherpaOnnxOnlineNemoCtcModelConfig(config, Module) {
   }
 }
 
+function initSherpaOnnxOnlineToneCtcModelConfig(config, Module) {
+  const n = Module.lengthBytesUTF8(config.model || '') + 1;
+  const buffer = Module._malloc(n);
+
+  const len = 1 * 4;  // 1 pointer
+  const ptr = Module._malloc(len);
+
+  Module.stringToUTF8(config.model || '', buffer, n);
+
+  Module.setValue(ptr, buffer, 'i8*');
+
+  return {
+    buffer: buffer, ptr: ptr, len: len,
+  }
+}
+
 function initSherpaOnnxOnlineModelConfig(config, Module) {
   if (!('transducer' in config)) {
     config.transducer = {
@@ -201,6 +221,12 @@ function initSherpaOnnxOnlineModelConfig(config, Module) {
     };
   }
 
+  if (!('toneCtc' in config)) {
+    config.toneCtc = {
+      model: '',
+    };
+  }
+
   if (!('tokensBuf' in config)) {
     config.tokensBuf = '';
   }
@@ -221,8 +247,11 @@ function initSherpaOnnxOnlineModelConfig(config, Module) {
   const nemoCtc =
       initSherpaOnnxOnlineNemoCtcModelConfig(config.nemoCtc, Module);
 
-  const len =
-      transducer.len + paraformer.len + zipformer2Ctc.len + 9 * 4 + nemoCtc.len;
+  const toneCtc =
+      initSherpaOnnxOnlineToneCtcModelConfig(config.toneCtc, Module);
+
+  const len = transducer.len + paraformer.len + zipformer2Ctc.len + 9 * 4 +
+      nemoCtc.len + toneCtc.len;
 
   const ptr = Module._malloc(len);
 
@@ -308,9 +337,13 @@ function initSherpaOnnxOnlineModelConfig(config, Module) {
   Module._CopyHeap(nemoCtc.ptr, nemoCtc.len, ptr + offset);
   offset += nemoCtc.len;
 
+  Module._CopyHeap(toneCtc.ptr, toneCtc.len, ptr + offset);
+  offset += toneCtc.len;
+
   return {
     buffer: buffer, ptr: ptr, len: len, transducer: transducer,
-        paraformer: paraformer, zipformer2Ctc: zipformer2Ctc, nemoCtc: nemoCtc
+        paraformer: paraformer, zipformer2Ctc: zipformer2Ctc, nemoCtc: nemoCtc,
+        toneCtc: toneCtc,
   }
 }
 
@@ -519,6 +552,10 @@ function createOnlineRecognizer(Module, myConfig) {
     model: '',
   };
 
+  const onlineToneCtcModelConfig = {
+    model: '',
+  };
+
   let type = 0;
 
   switch (type) {
@@ -541,6 +578,10 @@ function createOnlineRecognizer(Module, myConfig) {
       // nemoCtc
       onlineNemoCtcModelConfig.model = './nemo-ctc.onnx';
       break;
+    case 4:
+      // toneCtc
+      onlineToneCtcModelConfig.model = './tone-ctc.onnx';
+      break;
   }
 
 
@@ -549,6 +590,7 @@ function createOnlineRecognizer(Module, myConfig) {
     paraformer: onlineParaformerModelConfig,
     zipformer2Ctc: onlineZipformer2CtcModelConfig,
     nemoCtc: onlineNemoCtcModelConfig,
+    toneCtc: onlineToneCtcModelConfig,
     tokens: './tokens.txt',
     numThreads: 1,
     provider: 'cpu',
@@ -559,8 +601,8 @@ function createOnlineRecognizer(Module, myConfig) {
   };
 
   const featureConfig = {
-    sampleRate: 16000,
-    featureDim: 80,
+    sampleRate: 16000,  // it is ignored when toneCtc is used
+    featureDim: 80,     // it is ignored when toneCtc is used
   };
 
   let recognizerConfig = {

@@ -21,7 +21,8 @@ static_assert(sizeof(SherpaOnnxOnlineModelConfig) ==
                   sizeof(SherpaOnnxOnlineTransducerModelConfig) +
                       sizeof(SherpaOnnxOnlineParaformerModelConfig) +
                       sizeof(SherpaOnnxOnlineZipformer2CtcModelConfig) + 9 * 4 +
-                      sizeof(SherpaOnnxOnlineNemoCtcModelConfig),
+                      sizeof(SherpaOnnxOnlineNemoCtcModelConfig) +
+                      sizeof(SherpaOnnxOnlineToneCtcModelConfig),
               "");
 static_assert(sizeof(SherpaOnnxFeatureConfig) == 2 * 4, "");
 static_assert(sizeof(SherpaOnnxOnlineCtcFstDecoderConfig) == 2 * 4, "");
@@ -39,6 +40,7 @@ void MyPrint(SherpaOnnxOnlineRecognizerConfig *config) {
   auto paraformer_model_config = &model_config->paraformer;
   auto ctc_model_config = &model_config->zipformer2_ctc;
   auto nemo_ctc = &model_config->nemo_ctc;
+  auto t_one_ctc = &model_config->t_one_ctc;
 
   fprintf(stdout, "----------online transducer model config----------\n");
   fprintf(stdout, "encoder: %s\n", transducer_model_config->encoder);
@@ -55,6 +57,9 @@ void MyPrint(SherpaOnnxOnlineRecognizerConfig *config) {
   fprintf(stdout, "----------online nemo ctc model config----------\n");
   fprintf(stdout, "model: %s\n", nemo_ctc->model);
 
+  fprintf(stdout, "----------online t-one ctc model config----------\n");
+  fprintf(stdout, "model: %s\n", t_one_ctc->model);
+
   fprintf(stdout, "tokens: %s\n", model_config->tokens);
   fprintf(stdout, "num_threads: %d\n", model_config->num_threads);
   fprintf(stdout, "provider: %s\n", model_config->provider);

@@ -75,9 +75,10 @@ function initModelConfig(config, Module) {
   const paraformer_len = 2 * 4
   const zipfomer2_ctc_len = 1 * 4
   const nemo_ctc_len = 1 * 4
+  const t_one_ctc_len = 1 * 4
 
   const len = transducer.len + paraformer_len + zipfomer2_ctc_len + 9 * 4 +
-      nemo_ctc_len;
+      nemo_ctc_len + t_one_ctc_len;
 
   const ptr = Module._malloc(len);
   Module.HEAPU8.fill(0, ptr, ptr + len);
@@ -152,6 +153,7 @@ function initModelConfig(config, Module) {
 
   Module.setValue(ptr + offset, config.tokensBufSize || 0, 'i32');
   offset += 4;
+  // skip nemo_ctc and t_one_ctc
 
   return {
     buffer: buffer, ptr: ptr, len: len, transducer: transducer

@@ -20,7 +20,8 @@ static_assert(sizeof(SherpaOnnxOnlineModelConfig) ==
                   sizeof(SherpaOnnxOnlineTransducerModelConfig) +
                       sizeof(SherpaOnnxOnlineParaformerModelConfig) +
                       sizeof(SherpaOnnxOnlineZipformer2CtcModelConfig) + 9 * 4 +
-                      sizeof(SherpaOnnxOnlineNemoCtcModelConfig),
+                      sizeof(SherpaOnnxOnlineNemoCtcModelConfig) +
+                      sizeof(SherpaOnnxOnlineToneCtcModelConfig),
               "");
 static_assert(sizeof(SherpaOnnxFeatureConfig) == 2 * 4, "");
 static_assert(sizeof(SherpaOnnxKeywordSpotterConfig) ==