Add Kotlin and Java API for Dolphin CTC models (#2086)

@@ -23,8 +23,8 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest]
-        total: ["4"]
-        index: ["0", "1", "2", "3"]
+        total: ["16"]
+        index: ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15"]
 
     steps:
       - uses: actions/checkout@v4

@@ -23,8 +23,8 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest]
-        total: ["10"]
-        index: ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"]
+        total: ["18"]
+        index: ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17"]
 
     steps:
       - uses: actions/checkout@v4

@@ -105,6 +105,16 @@ jobs:
             make -j4
             ls -lh lib
 
+      - name:  Run java test (VAD + Non-streaming Dolphin CTC)
+        shell: bash
+        run: |
+          cd ./java-api-examples
+          ./run-vad-non-streaming-dolphin-ctc.sh
+          rm *.onnx
+          ls -lh *.wav
+          rm *.wav
+          rm -rf sherpa-onnx-dolphin-*
+
       - name:  Run speech enhancement (GTCRN)
         shell: bash
         run: |
@@ -135,6 +145,9 @@ jobs:
         run: |
           cd ./java-api-examples
 
+          ./run-non-streaming-decode-file-dolphin-ctc.sh
+          rm -rf sherpa-onnx-dolphin-*
+
           ./run-non-streaming-decode-file-moonshine.sh
           rm -rf sherpa-onnx-moonshine-*
 

@@ -140,3 +140,4 @@ README-DEV.txt
 *.jit
 ##clion
 .idea
+sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02

+// Copyright 2025 Xiaomi Corporation
+
+// This file shows how to use an offline Dolphin CTC model, i.e.,
+// non-streaming Dolphin CTC model, to decode files.
+import com.k2fsa.sherpa.onnx.*;
+
+public class NonStreamingDecodeFileDolphinCtc {
+  public static void main(String[] args) {
+    // please refer to
+    // https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+    // to download model files
+    String model = "./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx";
+    String tokens = "./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/tokens.txt";
+
+    String waveFilename =
+        "./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/test_wavs/0.wav";
+
+    WaveReader reader = new WaveReader(waveFilename);
+
+    OfflineDolphinModelConfig dolphin = OfflineDolphinModelConfig.builder().setModel(model).build();
+
+    OfflineModelConfig modelConfig =
+        OfflineModelConfig.builder()
+            .setDolphin(dolphin)
+            .setTokens(tokens)
+            .setNumThreads(1)
+            .setDebug(true)
+            .build();
+
+    OfflineRecognizerConfig config =
+        OfflineRecognizerConfig.builder()
+            .setOfflineModelConfig(modelConfig)
+            .setDecodingMethod("greedy_search")
+            .build();
+
+    OfflineRecognizer recognizer = new OfflineRecognizer(config);
+    OfflineStream stream = recognizer.createStream();
+    stream.acceptWaveform(reader.getSamples(), reader.getSampleRate());
+
+    recognizer.decode(stream);
+
+    String text = recognizer.getResult(stream).getText();
+
+    System.out.printf("filename:%s\nresult:%s\n", waveFilename, text);
+
+    stream.release();
+    recognizer.release();
+  }
+}

@@ -23,6 +23,7 @@ This directory contains examples for the JAVA API of sherpa-onnx.
 ## Non-Streaming Speech recognition
 
 ```bash
+./run-non-streaming-decode-file-dolphin-ctc.sh
 ./run-non-streaming-decode-file-paraformer.sh
 ./run-non-streaming-decode-file-sense-voice.sh
 ./run-non-streaming-decode-file-transducer.sh
@@ -102,6 +103,12 @@ The punctuation model supports both English and Chinese.
 ./run-vad-remove-slience.sh
 ```
 
+## VAD + Non-streaming Dolphin CTC for speech recognition
+
+```bash
+./run-vad-non-streaming-dolphin-ctc.sh
+```
+
 ## VAD + Non-streaming SenseVoice for speech recognition
 
 ```bash

+// Copyright 2025 Xiaomi Corporation
+
+// This file shows how to use a silero_vad model with a non-streaming Dolphin
+// CTC model for speech recognition.
+
+import com.k2fsa.sherpa.onnx.*;
+import java.util.Arrays;
+
+public class VadNonStreamingSenseVoice {
+  public static Vad createVad() {
+    // please download ./silero_vad.onnx from
+    // https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+    String model = "./silero_vad.onnx";
+    SileroVadModelConfig sileroVad =
+        SileroVadModelConfig.builder()
+            .setModel(model)
+            .setThreshold(0.5f)
+            .setMinSilenceDuration(0.25f)
+            .setMinSpeechDuration(0.5f)
+            .setWindowSize(512)
+            .setMaxSpeechDuration(5.0f)
+            .build();
+
+    VadModelConfig config =
+        VadModelConfig.builder()
+            .setSileroVadModelConfig(sileroVad)
+            .setSampleRate(16000)
+            .setNumThreads(1)
+            .setDebug(true)
+            .setProvider("cpu")
+            .build();
+
+    return new Vad(config);
+  }
+
+  public static OfflineRecognizer createOfflineRecognizer() {
+    // please refer to
+    // https://k2-fsa.github.io/sherpa/onnx/dolphin/index.html
+    // to download model files
+    String model = "./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx";
+    String tokens = "./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/tokens.txt";
+
+    OfflineDolphinModelConfig dolphin = OfflineDolphinModelConfig.builder().setModel(model).build();
+
+    OfflineModelConfig modelConfig =
+        OfflineModelConfig.builder()
+            .setDolphin(dolphin)
+            .setTokens(tokens)
+            .setNumThreads(1)
+            .setDebug(true)
+            .build();
+
+    OfflineRecognizerConfig config =
+        OfflineRecognizerConfig.builder()
+            .setOfflineModelConfig(modelConfig)
+            .setDecodingMethod("greedy_search")
+            .build();
+
+    return new OfflineRecognizer(config);
+  }
+
+  public static void main(String[] args) {
+
+    Vad vad = createVad();
+    OfflineRecognizer recognizer = createOfflineRecognizer();
+
+    // You can download the test file from
+    // https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+    String testWaveFilename = "./lei-jun-test.wav";
+    WaveReader reader = new WaveReader(testWaveFilename);
+
+    int numSamples = reader.getSamples().length;
+    int numIter = numSamples / 512;
+
+    for (int i = 0; i != numIter; ++i) {
+      int start = i * 512;
+      int end = start + 512;
+      float[] samples = Arrays.copyOfRange(reader.getSamples(), start, end);
+      vad.acceptWaveform(samples);
+      if (vad.isSpeechDetected()) {
+        while (!vad.empty()) {
+          SpeechSegment segment = vad.front();
+          float startTime = segment.getStart() / 16000.0f;
+          float duration = segment.getSamples().length / 16000.0f;
+
+          OfflineStream stream = recognizer.createStream();
+          stream.acceptWaveform(segment.getSamples(), 16000);
+          recognizer.decode(stream);
+          String text = recognizer.getResult(stream).getText();
+          stream.release();
+
+          if (!text.isEmpty()) {
+            System.out.printf("%.3f--%.3f: %s\n", startTime, startTime + duration, text);
+          }
+
+          vad.pop();
+        }
+      }
+    }
+
+    vad.flush();
+    while (!vad.empty()) {
+      SpeechSegment segment = vad.front();
+      float startTime = segment.getStart() / 16000.0f;
+      float duration = segment.getSamples().length / 16000.0f;
+
+      OfflineStream stream = recognizer.createStream();
+      stream.acceptWaveform(segment.getSamples(), 16000);
+      recognizer.decode(stream);
+      String text = recognizer.getResult(stream).getText();
+      stream.release();
+
+      if (!text.isEmpty()) {
+        System.out.printf("%.3f--%.3f: %s\n", startTime, startTime + duration, text);
+      }
+
+      vad.pop();
+    }
+
+    vad.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-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+  tar xvf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+  rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+  ls -lh sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02
+fi
+
+java \
+  -Djava.library.path=$PWD/../build/lib \
+  -cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
+  NonStreamingDecodeFileDolphinCtc.java

+#!/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 ./silero_vad.onnx ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
+fi
+
+if [ ! -f ./lei-jun-test.wav ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/lei-jun-test.wav
+fi
+
+if [ ! -f ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx ]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+  tar xvf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+  rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+  ls -lh sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02
+fi
+
+java \
+  -Djava.library.path=$PWD/../build/lib \
+  -cp ../sherpa-onnx/java-api/build/sherpa-onnx.jar \
+  ./VadNonStreamingDolphinCtc.java

@@ -190,6 +190,13 @@ function testSpokenLanguageIdentification() {
 }
 
 function testOfflineAsr() {
+  if [ ! -f ./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx ]; then
+    curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+    tar xvf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+    rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+    ls -lh sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02
+  fi
+
   if [ ! -f ./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/encoder.int8.onnx ]; then
     curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16.tar.bz2
     tar xvf sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16.tar.bz2

 package com.k2fsa.sherpa.onnx
 
 fun main() {
-  val types = arrayOf(0, 2, 5, 6, 15, 21, 24)
+  val types = arrayOf(0, 2, 5, 6, 15, 21, 24, 25)
   for (type in types) {
     test(type)
   }
@@ -18,6 +18,7 @@ fun test(type: Int) {
     15 -> "./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav"
     21 -> "./sherpa-onnx-moonshine-tiny-en-int8/test_wavs/0.wav"
     24 -> "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/0.wav"
+    25 -> "./sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/test_wavs/0.wav"
     else -> null
   }
 

@@ -160,6 +160,21 @@ def get_2nd_models():
             popd
             """,
         ),
+        Model(
+            model_name="sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02",
+            idx=25,
+            lang="multi_lang",
+            short_name="dolphin_base_ctc",
+            cmd="""
+            pushd $model_name
+
+            rm -rfv test_wavs
+
+            ls -lh
+
+            popd
+            """,
+        ),
     ]
     return models
 
@@ -304,6 +319,48 @@ def get_1st_models():
             popd
             """,
         ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01",
+            idx=15,
+            lang="zh",
+            short_name="int8_small_zipformer",
+            rule_fsts="itn_zh_number.fst",
+            cmd="""
+            if [ ! -f itn_zh_number.fst ]; then
+              curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/itn_zh_number.fst
+            fi
+            pushd $model_name
+            rm -f bpe.model
+
+            rm -rf test_wavs
+            rm README.md
+
+            ls -lh
+
+            popd
+            """,
+        ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-small-ctc-zh-2025-04-01",
+            idx=16,
+            lang="zh",
+            short_name="small_zipformer",
+            rule_fsts="itn_zh_number.fst",
+            cmd="""
+            if [ ! -f itn_zh_number.fst ]; then
+              curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/itn_zh_number.fst
+            fi
+            pushd $model_name
+            rm -f bpe.model
+
+            rm -rf test_wavs
+            rm README.md
+
+            ls -lh
+
+            popd
+            """,
+        ),
     ]
 
     return models
@@ -313,19 +370,25 @@ def get_models():
     first = get_1st_models()
     second = get_2nd_models()
 
-    combinations = [
-        (
+    combinations = []
+
+    first_zh = [
         "sherpa-onnx-streaming-zipformer-zh-14M-2023-02-23",
+        "sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01",
+        "sherpa-onnx-streaming-zipformer-small-ctc-zh-2025-04-01",
+    ]
+
+    second_zh = [
         "sherpa-onnx-paraformer-zh-2023-09-14",
-        ),
-        (
-            "sherpa-onnx-streaming-zipformer-zh-14M-2023-02-23",
         "icefall-asr-zipformer-wenetspeech-20230615",
-        ),
-        (
-            "sherpa-onnx-streaming-zipformer-zh-14M-2023-02-23",
         "sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17",
-        ),
+        "sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02",
+    ]
+    for first_m in first_zh:
+        for second_m in second_zh:
+            combinations.append((first_m, second_m))
+
+    combinations += [
         (
             "sherpa-onnx-streaming-zipformer-en-20M-2023-02-17",
             "sherpa-onnx-whisper-tiny.en",

@@ -263,6 +263,48 @@ def get_models():
             popd
             """,
         ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01",
+            idx=15,
+            lang="zh",
+            short_name="int8_small_zipformer",
+            rule_fsts="itn_zh_number.fst",
+            cmd="""
+            if [ ! -f itn_zh_number.fst ]; then
+              curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/itn_zh_number.fst
+            fi
+            pushd $model_name
+            rm -f bpe.model
+
+            rm -rf test_wavs
+            rm README.md
+
+            ls -lh
+
+            popd
+            """,
+        ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-small-ctc-zh-2025-04-01",
+            idx=16,
+            lang="zh",
+            short_name="small_zipformer",
+            rule_fsts="itn_zh_number.fst",
+            cmd="""
+            if [ ! -f itn_zh_number.fst ]; then
+              curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/itn_zh_number.fst
+            fi
+            pushd $model_name
+            rm -f bpe.model
+
+            rm -rf test_wavs
+            rm README.md
+
+            ls -lh
+
+            popd
+            """,
+        ),
     ]
 
     return models

@@ -443,6 +443,22 @@ def get_models():
             popd
             """,
         ),
+        Model(
+            model_name="sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02",
+            idx=25,
+            lang="multi_lang",
+            lang2="multi_lang",
+            short_name="multi_lang",
+            cmd="""
+            pushd $model_name
+
+            rm -rfv test_wavs
+
+            ls -lh
+
+            popd
+            """,
+        ),
     ]
     return models
 

@@ -30,6 +30,7 @@ java_files += OfflineFireRedAsrModelConfig.java
 java_files += OfflineMoonshineModelConfig.java
 java_files += OfflineNemoEncDecCtcModelConfig.java
 java_files += OfflineSenseVoiceModelConfig.java
+java_files += OfflineDolphinModelConfig.java
 java_files += OfflineModelConfig.java
 java_files += OfflineRecognizerConfig.java
 java_files += OfflineRecognizerResult.java

+// Copyright 2025 Xiaomi Corporation
+
+package com.k2fsa.sherpa.onnx;
+
+public class OfflineDolphinModelConfig {
+    private final String model;
+
+    private OfflineDolphinModelConfig(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 OfflineDolphinModelConfig build() {
+            return new OfflineDolphinModelConfig(this);
+        }
+
+        public Builder setModel(String model) {
+            this.model = model;
+            return this;
+        }
+    }
+}
\ No newline at end of file

@@ -10,6 +10,7 @@ public class OfflineModelConfig {
     private final OfflineMoonshineModelConfig moonshine;
     private final OfflineNemoEncDecCtcModelConfig nemo;
     private final OfflineSenseVoiceModelConfig senseVoice;
+    private final OfflineDolphinModelConfig dolphin;
     private final String teleSpeech;
     private final String tokens;
     private final int numThreads;
@@ -28,6 +29,7 @@ public class OfflineModelConfig {
         this.moonshine = builder.moonshine;
         this.nemo = builder.nemo;
         this.senseVoice = builder.senseVoice;
+        this.dolphin = builder.dolphin;
         this.teleSpeech = builder.teleSpeech;
         this.tokens = builder.tokens;
         this.numThreads = builder.numThreads;
@@ -62,6 +64,10 @@ public class OfflineModelConfig {
         return senseVoice;
     }
 
+    public OfflineDolphinModelConfig getDolphin() {
+        return dolphin;
+    }
+
     public String getTokens() {
         return tokens;
     }
@@ -102,6 +108,7 @@ public class OfflineModelConfig {
         private OfflineMoonshineModelConfig moonshine = OfflineMoonshineModelConfig.builder().build();
         private OfflineNemoEncDecCtcModelConfig nemo = OfflineNemoEncDecCtcModelConfig.builder().build();
         private OfflineSenseVoiceModelConfig senseVoice = OfflineSenseVoiceModelConfig.builder().build();
+        private OfflineDolphinModelConfig dolphin = OfflineDolphinModelConfig.builder().build();
         private String teleSpeech = "";
         private String tokens = "";
         private int numThreads = 1;
@@ -120,6 +127,11 @@ public class OfflineModelConfig {
             return this;
         }
 
+        public Builder setDolphin(OfflineDolphinModelConfig dolphin) {
+            this.dolphin = dolphin;
+            return this;
+        }
+
         public Builder setParaformer(OfflineParaformerModelConfig paraformer) {
             this.paraformer = paraformer;
             return this;

@@ -265,6 +265,19 @@ static OfflineRecognizerConfig GetOfflineConfig(JNIEnv *env, jobject config) {
   ans.model_config.nemo_ctc.model = p;
   env->ReleaseStringUTFChars(s, p);
 
+  // dolphin
+  fid = env->GetFieldID(model_config_cls, "dolphin",
+                        "Lcom/k2fsa/sherpa/onnx/OfflineDolphinModelConfig;");
+  jobject dolphin_config = env->GetObjectField(model_config, fid);
+  jclass dolphin_config_cls = env->GetObjectClass(dolphin_config);
+
+  fid = env->GetFieldID(nemo_config_cls, "model", "Ljava/lang/String;");
+
+  s = (jstring)env->GetObjectField(dolphin_config, fid);
+  p = env->GetStringUTFChars(s, nullptr);
+  ans.model_config.dolphin.model = p;
+  env->ReleaseStringUTFChars(s, p);
+
   fid = env->GetFieldID(model_config_cls, "teleSpeech", "Ljava/lang/String;");
   s = (jstring)env->GetObjectField(model_config, fid);
   p = env->GetStringUTFChars(s, nullptr);

@@ -25,6 +25,10 @@ data class OfflineNemoEncDecCtcModelConfig(
     var model: String = "",
 )
 
+data class OfflineDolphinModelConfig(
+    var model: String = "",
+)
+
 data class OfflineWhisperModelConfig(
     var encoder: String = "",
     var decoder: String = "",
@@ -59,6 +63,7 @@ data class OfflineModelConfig(
     var moonshine: OfflineMoonshineModelConfig = OfflineMoonshineModelConfig(),
     var nemo: OfflineNemoEncDecCtcModelConfig = OfflineNemoEncDecCtcModelConfig(),
     var senseVoice: OfflineSenseVoiceModelConfig = OfflineSenseVoiceModelConfig(),
+    var dolphin: OfflineDolphinModelConfig = OfflineDolphinModelConfig(),
     var teleSpeech: String = "",
     var numThreads: Int = 1,
     var debug: Boolean = false,
@@ -481,6 +486,16 @@ fun getOfflineModelConfig(type: Int): OfflineModelConfig? {
                 tokens = "$modelDir/tokens.txt",
             )
         }
+
+        25 -> {
+            val modelDir = "sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02"
+            return OfflineModelConfig(
+                dolphin = OfflineDolphinModelConfig(
+                    model = "$modelDir/model.int8.onnx",
+                ),
+                tokens = "$modelDir/tokens.txt",
+            )
+        }
     }
     return null
 }

@@ -374,6 +374,26 @@ fun getModelConfig(type: Int): OnlineModelConfig? {
                 modelType = "zipformer",
             )
         }
+
+        15 -> {
+            val modelDir = "sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01"
+            return OnlineModelConfig(
+                zipformer2Ctc = OnlineZipformer2CtcModelConfig(
+                    model = "$modelDir/model.int8.onnx",
+                ),
+                tokens = "$modelDir/tokens.txt",
+            )
+        }
+
+        16 -> {
+            val modelDir = "sherpa-onnx-streaming-zipformer-small-ctc-zh-2025-04-01"
+            return OnlineModelConfig(
+                zipformer2Ctc = OnlineZipformer2CtcModelConfig(
+                    model = "$modelDir/model.onnx",
+                ),
+                tokens = "$modelDir/tokens.txt",
+            )
+        }
     }
     return null
 }