Add C++ and Python API for Kokoro TTS models. (#1715)

Fangjun Kuang · GitHub
Commit ffc6b480a0564fbd5d0a675e4af9a268cb385bc3 ffc6b480 1 parent 9efe26a6
.github/scripts/test-offline-tts.sh
.github/scripts/test-python.sh
python-api-examples/offline-tts-play.py
python-api-examples/offline-tts.py
sherpa-onnx/csrc/CMakeLists.txt
sherpa-onnx/csrc/melo-tts-lexicon.h
sherpa-onnx/csrc/offline-tts-character-frontend.h
sherpa-onnx/csrc/offline-tts-impl.cc
sherpa-onnx/csrc/offline-tts-kokoro-impl.h
sherpa-onnx/csrc/offline-tts-kokoro-model-config.cc
sherpa-onnx/csrc/offline-tts-kokoro-model-config.h
sherpa-onnx/csrc/offline-tts-kokoro-model-meta-data.h
sherpa-onnx/csrc/offline-tts-kokoro-model.cc
sherpa-onnx/csrc/offline-tts-kokoro-model.h
sherpa-onnx/csrc/offline-tts-matcha-model-metadata.h → sherpa-onnx/csrc/offline-tts-matcha-model-meta-data.h
sherpa-onnx/csrc/offline-tts-matcha-model.h
sherpa-onnx/csrc/offline-tts-model-config.cc
sherpa-onnx/csrc/offline-tts-model-config.h
sherpa-onnx/csrc/offline-tts-vits-model-metadata.h → sherpa-onnx/csrc/offline-tts-vits-model-meta-data.h
sherpa-onnx/csrc/offline-tts-vits-model.h
--- a/.github/scripts/test-offline-tts.sh
查看文件 @ffc6b48
+++ b/.github/scripts/test-offline-tts.sh
查看文件 @ffc6b48
@@ -19,6 +19,31 @@ which $EXE
 mkdir ./tts
 log "------------------------------------------------------------"
+log "kokoro-en-v0_19"
+log "------------------------------------------------------------"
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/kokoro-en-v0_19.tar.bz2
+tar xf kokoro-en-v0_19.tar.bz2
+rm kokoro-en-v0_19.tar.bz2
+
+# mapping of sid to voice name
+# 0->af, 1->af_bella, 2->af_nicole, 3->af_sarah, 4->af_sky, 5->am_adam
+# 6->am_michael, 7->bf_emma, 8->bf_isabella, 9->bm_george, 10->bm_lewis
+
+for sid in $(seq 0 10); do
+  $EXE \
+    --debug=1 \
+    --kokoro-model=./kokoro-en-v0_19/model.onnx \
+    --kokoro-voices=./kokoro-en-v0_19/voices.bin \
+    --kokoro-tokens=./kokoro-en-v0_19/tokens.txt \
+    --kokoro-data-dir=./kokoro-en-v0_19/espeak-ng-data \
+    --num-threads=2 \
+    --sid=$sid \
+    --output-filename="./tts/kokoro-$sid.wav" \
+    "Today as always, men fall into two groups: slaves and free men. Whoever does not have two-thirds of his day for himself, is a slave, whatever he may be  a statesman, a businessman, an official, or a scholar."
+done
+rm -rf kokoro-en-v0_19
+
+log "------------------------------------------------------------"
 log "matcha-icefall-en_US-ljspeech"
 log "------------------------------------------------------------"
 curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/matcha-icefall-en_US-ljspeech.tar.bz2
--- a/.github/scripts/test-python.sh
查看文件 @ffc6b48
+++ b/.github/scripts/test-python.sh
查看文件 @ffc6b48
@@ -267,6 +267,25 @@ log "Offline TTS test"
 # test waves are saved in ./tts
 mkdir ./tts
+log "kokoro-en-v0_19 test"
+
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/kokoro-en-v0_19.tar.bz2
+tar xf kokoro-en-v0_19.tar.bz2
+rm kokoro-en-v0_19.tar.bz2
+
+python3 ./python-api-examples/offline-tts.py \
+  --debug=1 \
+  --kokoro-model=./kokoro-en-v0_19/model.onnx \
+  --kokoro-voices=./kokoro-en-v0_19/voices.bin \
+  --kokoro-tokens=./kokoro-en-v0_19/tokens.txt \
+  --kokoro-data-dir=./kokoro-en-v0_19/espeak-ng-data \
+  --num-threads=2 \
+  --sid=10 \
+  --output-filename="./tts/kokoro-10.wav" \
+  "Today as always, men fall into two groups: slaves and free men. Whoever does not have two-thirds of his day for himself, is a slave, whatever he may be  a statesman, a businessman, an official, or a scholar."
+
+rm -rf kokoro-en-v0_19
+
 log "matcha-ljspeech-en test"
 curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/matcha-icefall-en_US-ljspeech.tar.bz2
--- a/python-api-examples/offline-tts-play.py
查看文件 @ffc6b48
+++ b/python-api-examples/offline-tts-play.py
查看文件 @ffc6b48
@@ -11,7 +11,7 @@ while the model is still generating.
 Usage:
-Example (1/5)
+Example (1/6)
 wget https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/vits-piper-en_US-amy-low.tar.bz2
 tar xf vits-piper-en_US-amy-low.tar.bz2
@@ -23,7 +23,7 @@ python3 ./python-api-examples/offline-tts-play.py \
  --output-filename=./generated.wav \
  "Today as always, men fall into two groups: slaves and free men. Whoever does not have two-thirds of his day for himself, is a slave, whatever he may be: a statesman, a businessman, an official, or a scholar."
-Example (2/5)
+Example (2/6)
 wget https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/vits-zh-aishell3.tar.bz2
 tar xvf vits-zh-aishell3.tar.bz2
@@ -37,7 +37,7 @@ python3 ./python-api-examples/offline-tts-play.py \
  --output-filename=./liubei-21.wav \
  "勿以恶小而为之，勿以善小而不为。惟贤惟德，能服于人。122334"
-Example (3/5)
+Example (3/6)
 wget https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/sherpa-onnx-vits-zh-ll.tar.bz2
 tar xvf sherpa-onnx-vits-zh-ll.tar.bz2
@@ -53,7 +53,7 @@ python3 ./python-api-examples/offline-tts-play.py \
  --output-filename=./test-2.wav \
  "当夜幕降临，星光点点，伴随着微风拂面，我在静谧中感受着时光的流转，思念如涟漪荡漾，梦境如画卷展开，我与自然融为一体，沉静在这片宁静的美丽之中，感受着生命的奇迹与温柔。2024年5月11号，拨打110或者18920240511。123456块钱。"
-Example (4/5)
+Example (4/6)
 curl -O -SL https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/matcha-icefall-zh-baker.tar.bz2
 tar xvf matcha-icefall-zh-baker.tar.bz2
@@ -71,7 +71,7 @@ python3 ./python-api-examples/offline-tts-play.py \
  --output-filename=./test-matcha.wav \
  "某某银行的副行长和一些行政领导表示，他们去过长江和长白山; 经济不断增长。2024年12月31号，拨打110或者18920240511。123456块钱。"
-Example (5/5)
+Example (5/6)
 curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/matcha-icefall-en_US-ljspeech.tar.bz2
 tar xvf matcha-icefall-en_US-ljspeech.tar.bz2
@@ -88,6 +88,22 @@ python3 ./python-api-examples/offline-tts-play.py \
   --num-threads=2 \
  "Today as always, men fall into two groups: slaves and free men. Whoever does not have two-thirds of his day for himself, is a slave, whatever he may be: a statesman, a businessman, an official, or a scholar."
+Example (6/6)
+
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/kokoro-en-v0_19.tar.bz2
+tar xf kokoro-en-v0_19.tar.bz2
+rm kokoro-en-v0_19.tar.bz2
+
+python3 ./python-api-examples/offline-tts.py \
+  --debug=1 \
+  --kokoro-model=./kokoro-en-v0_19/model.onnx \
+  --kokoro-voices=./kokoro-en-v0_19/voices.bin \
+  --kokoro-tokens=./kokoro-en-v0_19/tokens.txt \
+  --kokoro-data-dir=./kokoro-en-v0_19/espeak-ng-data \
+  --num-threads=2 \
+  --sid=10 \
+  --output-filename="./kokoro-10.wav" \
+  "Today as always, men fall into two groups: slaves and free men. Whoever does not have two-thirds of his day for himself, is a slave, whatever he may be  a statesman, a businessman, an official, or a scholar."
 You can find more models at
 https://github.com/k2-fsa/sherpa-onnx/releases/tag/tts-models
@@ -202,6 +218,36 @@ def add_matcha_args(parser):
     )
+def add_kokoro_args(parser):
+    parser.add_argument(
+        "--kokoro-model",
+        type=str,
+        default="",
+        help="Path to model.onnx for kokoro",
+    )
+
+    parser.add_argument(
+        "--kokoro-voices",
+        type=str,
+        default="",
+        help="Path to voices.bin for kokoro",
+    )
+
+    parser.add_argument(
+        "--kokoro-tokens",
+        type=str,
+        default="",
+        help="Path to tokens.txt for kokoro",
+    )
+
+    parser.add_argument(
+        "--kokoro-data-dir",
+        type=str,
+        default="",
+        help="Path to the dict directory of espeak-ng.",
+    )
+
+
 def get_args():
     parser = argparse.ArgumentParser(
         formatter_class=argparse.ArgumentDefaultsHelpFormatter
@@ -209,6 +255,7 @@ def get_args():
     add_vits_args(parser)
     add_matcha_args(parser)
+    add_kokoro_args(parser)
     parser.add_argument(
         "--tts-rule-fsts",
@@ -407,6 +454,12 @@ def main():
                 data_dir=args.matcha_data_dir,
                 dict_dir=args.matcha_dict_dir,
             ),
+            kokoro=sherpa_onnx.OfflineTtsKokoroModelConfig(
+                model=args.kokoro_model,
+                voices=args.kokoro_voices,
+                tokens=args.kokoro_tokens,
+                data_dir=args.kokoro_data_dir,
+            ),
             provider=args.provider,
             debug=args.debug,
             num_threads=args.num_threads,
--- a/python-api-examples/offline-tts.py
查看文件 @ffc6b48
+++ b/python-api-examples/offline-tts.py
查看文件 @ffc6b48
@@ -12,7 +12,7 @@ generated audio.
 Usage:
-Example (1/5)
+Example (1/6)
 wget https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/vits-piper-en_US-amy-low.tar.bz2
 tar xf vits-piper-en_US-amy-low.tar.bz2
@@ -24,7 +24,7 @@ python3 ./python-api-examples/offline-tts.py \
  --output-filename=./generated.wav \
  "Today as always, men fall into two groups: slaves and free men. Whoever does not have two-thirds of his day for himself, is a slave, whatever he may be: a statesman, a businessman, an official, or a scholar."
-Example (2/5)
+Example (2/6)
 wget https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/vits-icefall-zh-aishell3.tar.bz2
 tar xvf vits-icefall-zh-aishell3.tar.bz2
@@ -38,7 +38,7 @@ python3 ./python-api-examples/offline-tts.py \
  --output-filename=./liubei-21.wav \
  "勿以恶小而为之，勿以善小而不为。惟贤惟德，能服于人。122334"
-Example (3/5)
+Example (3/6)
 wget https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/sherpa-onnx-vits-zh-ll.tar.bz2
 tar xvf sherpa-onnx-vits-zh-ll.tar.bz2
@@ -54,7 +54,7 @@ python3 ./python-api-examples/offline-tts.py \
  --output-filename=./test-2.wav \
  "当夜幕降临，星光点点，伴随着微风拂面，我在静谧中感受着时光的流转，思念如涟漪荡漾，梦境如画卷展开，我与自然融为一体，沉静在这片宁静的美丽之中，感受着生命的奇迹与温柔。2024年5月11号，拨打110或者18920240511。123456块钱。"
-Example (4/5)
+Example (4/6)
 curl -O -SL https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/matcha-icefall-zh-baker.tar.bz2
 tar xvf matcha-icefall-zh-baker.tar.bz2
@@ -72,7 +72,7 @@ python3 ./python-api-examples/offline-tts.py \
  --output-filename=./test-matcha.wav \
  "某某银行的副行长和一些行政领导表示，他们去过长江和长白山; 经济不断增长。2024年12月31号，拨打110或者18920240511。123456块钱。"
-Example (5/5)
+Example (5/6)
 curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/matcha-icefall-en_US-ljspeech.tar.bz2
 tar xvf matcha-icefall-en_US-ljspeech.tar.bz2
@@ -89,6 +89,23 @@ python3 ./python-api-examples/offline-tts.py \
   --num-threads=2 \
  "Today as always, men fall into two groups: slaves and free men. Whoever does not have two-thirds of his day for himself, is a slave, whatever he may be: a statesman, a businessman, an official, or a scholar."
+Example (6/6)
+
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/kokoro-en-v0_19.tar.bz2
+tar xf kokoro-en-v0_19.tar.bz2
+rm kokoro-en-v0_19.tar.bz2
+
+python3 ./python-api-examples/offline-tts.py \
+  --debug=1 \
+  --kokoro-model=./kokoro-en-v0_19/model.onnx \
+  --kokoro-voices=./kokoro-en-v0_19/voices.bin \
+  --kokoro-tokens=./kokoro-en-v0_19/tokens.txt \
+  --kokoro-data-dir=./kokoro-en-v0_19/espeak-ng-data \
+  --num-threads=2 \
+  --sid=10 \
+  --output-filename="./kokoro-10.wav" \
+  "Today as always, men fall into two groups: slaves and free men. Whoever does not have two-thirds of his day for himself, is a slave, whatever he may be  a statesman, a businessman, an official, or a scholar."
+
 You can find more models at
 https://github.com/k2-fsa/sherpa-onnx/releases/tag/tts-models
@@ -188,6 +205,36 @@ def add_matcha_args(parser):
     )
+def add_kokoro_args(parser):
+    parser.add_argument(
+        "--kokoro-model",
+        type=str,
+        default="",
+        help="Path to model.onnx for kokoro",
+    )
+
+    parser.add_argument(
+        "--kokoro-voices",
+        type=str,
+        default="",
+        help="Path to voices.bin for kokoro",
+    )
+
+    parser.add_argument(
+        "--kokoro-tokens",
+        type=str,
+        default="",
+        help="Path to tokens.txt for kokoro",
+    )
+
+    parser.add_argument(
+        "--kokoro-data-dir",
+        type=str,
+        default="",
+        help="Path to the dict directory of espeak-ng.",
+    )
+
+
 def get_args():
     parser = argparse.ArgumentParser(
         formatter_class=argparse.ArgumentDefaultsHelpFormatter
@@ -195,6 +242,7 @@ def get_args():
     add_vits_args(parser)
     add_matcha_args(parser)
+    add_kokoro_args(parser)
     parser.add_argument(
         "--tts-rule-fsts",
@@ -206,7 +254,7 @@ def get_args():
     parser.add_argument(
         "--max-num-sentences",
         type=int,
-        default=2,
+        default=1,
         help="""Max number of sentences in a batch to avoid OOM if the input
         text is very long. Set it to -1 to process all the sentences in a
         single batch. A smaller value does not mean it is slower compared
@@ -289,6 +337,12 @@ def main():
                 data_dir=args.matcha_data_dir,
                 dict_dir=args.matcha_dict_dir,
             ),
+            kokoro=sherpa_onnx.OfflineTtsKokoroModelConfig(
+                model=args.kokoro_model,
+                voices=args.kokoro_voices,
+                tokens=args.kokoro_tokens,
+                data_dir=args.kokoro_data_dir,
+            ),
             provider=args.provider,
             debug=args.debug,
             num_threads=args.num_threads,
--- a/sherpa-onnx/csrc/CMakeLists.txt
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/CMakeLists.txt
查看文件 @ffc6b48
@@ -158,6 +158,8 @@ if(SHERPA_ONNX_ENABLE_TTS)
     offline-tts-character-frontend.cc
     offline-tts-frontend.cc
     offline-tts-impl.cc
+    offline-tts-kokoro-model-config.cc
+    offline-tts-kokoro-model.cc
     offline-tts-matcha-model-config.cc
     offline-tts-matcha-model.cc
     offline-tts-model-config.cc
--- a/sherpa-onnx/csrc/melo-tts-lexicon.h
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/melo-tts-lexicon.h
查看文件 @ffc6b48
@@ -11,7 +11,7 @@
 #include <vector>
 #include "sherpa-onnx/csrc/offline-tts-frontend.h"
-#include "sherpa-onnx/csrc/offline-tts-vits-model-metadata.h"
+#include "sherpa-onnx/csrc/offline-tts-vits-model-meta-data.h"
 namespace sherpa_onnx {
--- a/sherpa-onnx/csrc/offline-tts-character-frontend.h
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-character-frontend.h
查看文件 @ffc6b48
@@ -10,7 +10,7 @@
 #include <vector>
 #include "sherpa-onnx/csrc/offline-tts-frontend.h"
-#include "sherpa-onnx/csrc/offline-tts-vits-model-metadata.h"
+#include "sherpa-onnx/csrc/offline-tts-vits-model-meta-data.h"
 namespace sherpa_onnx {
--- a/sherpa-onnx/csrc/offline-tts-impl.cc
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-impl.cc
查看文件 @ffc6b48
@@ -16,6 +16,7 @@
 #include "rawfile/raw_file_manager.h"
 #endif
+#include "sherpa-onnx/csrc/offline-tts-kokoro-impl.h"
 #include "sherpa-onnx/csrc/offline-tts-matcha-impl.h"
 #include "sherpa-onnx/csrc/offline-tts-vits-impl.h"
@@ -37,8 +38,11 @@ std::unique_ptr<OfflineTtsImpl> OfflineTtsImpl::Create(
     const OfflineTtsConfig &config) {
   if (!config.model.vits.model.empty()) {
     return std::make_unique<OfflineTtsVitsImpl>(config);
+  } else if (!config.model.matcha.acoustic_model.empty()) {
+    return std::make_unique<OfflineTtsMatchaImpl>(config);
   }
-  return std::make_unique<OfflineTtsMatchaImpl>(config);
+
+  return std::make_unique<OfflineTtsKokoroImpl>(config);
 }
 template <typename Manager>
@@ -46,9 +50,11 @@ std::unique_ptr<OfflineTtsImpl> OfflineTtsImpl::Create(
     Manager *mgr, const OfflineTtsConfig &config) {
   if (!config.model.vits.model.empty()) {
     return std::make_unique<OfflineTtsVitsImpl>(mgr, config);
+  } else if (!config.model.matcha.acoustic_model.empty()) {
+    return std::make_unique<OfflineTtsMatchaImpl>(mgr, config);
   }
-  return std::make_unique<OfflineTtsMatchaImpl>(mgr, config);
+  return std::make_unique<OfflineTtsKokoroImpl>(mgr, config);
 }
 #if __ANDROID_API__ >= 9
--- a/sherpa-onnx/csrc/offline-tts-kokoro-impl.h 0 → 100644
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-kokoro-impl.h 0 → 100644
查看文件 @ffc6b48
+// sherpa-onnx/csrc/offline-tts-kokoro-impl.h
+//
+// Copyright (c)  2025  Xiaomi Corporation
+#ifndef SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_IMPL_H_
+#define SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_IMPL_H_
+
+#include <memory>
+#include <string>
+#include <strstream>
+#include <utility>
+#include <vector>
+
+#include "fst/extensions/far/far.h"
+#include "kaldifst/csrc/kaldi-fst-io.h"
+#include "kaldifst/csrc/text-normalizer.h"
+#include "sherpa-onnx/csrc/lexicon.h"
+#include "sherpa-onnx/csrc/macros.h"
+#include "sherpa-onnx/csrc/offline-tts-frontend.h"
+#include "sherpa-onnx/csrc/offline-tts-impl.h"
+#include "sherpa-onnx/csrc/offline-tts-kokoro-model.h"
+#include "sherpa-onnx/csrc/onnx-utils.h"
+#include "sherpa-onnx/csrc/piper-phonemize-lexicon.h"
+#include "sherpa-onnx/csrc/text-utils.h"
+
+namespace sherpa_onnx {
+
+class OfflineTtsKokoroImpl : public OfflineTtsImpl {
+ public:
+  explicit OfflineTtsKokoroImpl(const OfflineTtsConfig &config)
+      : config_(config),
+        model_(std::make_unique<OfflineTtsKokoroModel>(config.model)) {
+    InitFrontend();
+
+    if (!config.rule_fsts.empty()) {
+      std::vector<std::string> files;
+      SplitStringToVector(config.rule_fsts, ",", false, &files);
+      tn_list_.reserve(files.size());
+      for (const auto &f : files) {
+        if (config.model.debug) {
+#if __OHOS__
+          SHERPA_ONNX_LOGE("rule fst: %{public}s", f.c_str());
+#else
+          SHERPA_ONNX_LOGE("rule fst: %s", f.c_str());
+#endif
+        }
+        tn_list_.push_back(std::make_unique<kaldifst::TextNormalizer>(f));
+      }
+    }
+
+    if (!config.rule_fars.empty()) {
+      if (config.model.debug) {
+        SHERPA_ONNX_LOGE("Loading FST archives");
+      }
+      std::vector<std::string> files;
+      SplitStringToVector(config.rule_fars, ",", false, &files);
+
+      tn_list_.reserve(files.size() + tn_list_.size());
+
+      for (const auto &f : files) {
+        if (config.model.debug) {
+#if __OHOS__
+          SHERPA_ONNX_LOGE("rule far: %{public}s", f.c_str());
+#else
+          SHERPA_ONNX_LOGE("rule far: %s", f.c_str());
+#endif
+        }
+        std::unique_ptr<fst::FarReader<fst::StdArc>> reader(
+            fst::FarReader<fst::StdArc>::Open(f));
+        for (; !reader->Done(); reader->Next()) {
+          std::unique_ptr<fst::StdConstFst> r(
+              fst::CastOrConvertToConstFst(reader->GetFst()->Copy()));
+
+          tn_list_.push_back(
+              std::make_unique<kaldifst::TextNormalizer>(std::move(r)));
+        }
+      }
+
+      if (config.model.debug) {
+        SHERPA_ONNX_LOGE("FST archives loaded!");
+      }
+    }
+  }
+
+  template <typename Manager>
+  OfflineTtsKokoroImpl(Manager *mgr, const OfflineTtsConfig &config)
+      : config_(config),
+        model_(std::make_unique<OfflineTtsKokoroModel>(mgr, config.model)) {
+    InitFrontend(mgr);
+
+    if (!config.rule_fsts.empty()) {
+      std::vector<std::string> files;
+      SplitStringToVector(config.rule_fsts, ",", false, &files);
+      tn_list_.reserve(files.size());
+      for (const auto &f : files) {
+        if (config.model.debug) {
+#if __OHOS__
+          SHERPA_ONNX_LOGE("rule fst: %{public}s", f.c_str());
+#else
+          SHERPA_ONNX_LOGE("rule fst: %s", f.c_str());
+#endif
+        }
+        auto buf = ReadFile(mgr, f);
+        std::istrstream is(buf.data(), buf.size());
+        tn_list_.push_back(std::make_unique<kaldifst::TextNormalizer>(is));
+      }
+    }
+
+    if (!config.rule_fars.empty()) {
+      std::vector<std::string> files;
+      SplitStringToVector(config.rule_fars, ",", false, &files);
+      tn_list_.reserve(files.size() + tn_list_.size());
+
+      for (const auto &f : files) {
+        if (config.model.debug) {
+#if __OHOS__
+          SHERPA_ONNX_LOGE("rule far: %{public}s", f.c_str());
+#else
+          SHERPA_ONNX_LOGE("rule far: %s", f.c_str());
+#endif
+        }
+
+        auto buf = ReadFile(mgr, f);
+
+        std::unique_ptr<std::istream> s(
+            new std::istrstream(buf.data(), buf.size()));
+
+        std::unique_ptr<fst::FarReader<fst::StdArc>> reader(
+            fst::FarReader<fst::StdArc>::Open(std::move(s)));
+
+        for (; !reader->Done(); reader->Next()) {
+          std::unique_ptr<fst::StdConstFst> r(
+              fst::CastOrConvertToConstFst(reader->GetFst()->Copy()));
+
+          tn_list_.push_back(
+              std::make_unique<kaldifst::TextNormalizer>(std::move(r)));
+        }  // for (; !reader->Done(); reader->Next())
+      }    // for (const auto &f : files)
+    }      // if (!config.rule_fars.empty())
+  }
+
+  int32_t SampleRate() const override {
+    return model_->GetMetaData().sample_rate;
+  }
+
+  int32_t NumSpeakers() const override {
+    return model_->GetMetaData().num_speakers;
+  }
+
+  GeneratedAudio Generate(
+      const std::string &_text, int64_t sid = 0, float speed = 1.0,
+      GeneratedAudioCallback callback = nullptr) const override {
+    const auto &meta_data = model_->GetMetaData();
+    int32_t num_speakers = meta_data.num_speakers;
+
+    if (num_speakers == 0 && sid != 0) {
+#if __OHOS__
+      SHERPA_ONNX_LOGE(
+          "This is a single-speaker model and supports only sid 0. Given sid: "
+          "%{public}d. sid is ignored",
+          static_cast<int32_t>(sid));
+#else
+      SHERPA_ONNX_LOGE(
+          "This is a single-speaker model and supports only sid 0. Given sid: "
+          "%d. sid is ignored",
+          static_cast<int32_t>(sid));
+#endif
+    }
+
+    if (num_speakers != 0 && (sid >= num_speakers || sid < 0)) {
+#if __OHOS__
+      SHERPA_ONNX_LOGE(
+          "This model contains only %{public}d speakers. sid should be in the "
+          "range [%{public}d, %{public}d]. Given: %{public}d. Use sid=0",
+          num_speakers, 0, num_speakers - 1, static_cast<int32_t>(sid));
+#else
+      SHERPA_ONNX_LOGE(
+          "This model contains only %d speakers. sid should be in the range "
+          "[%d, %d]. Given: %d. Use sid=0",
+          num_speakers, 0, num_speakers - 1, static_cast<int32_t>(sid));
+#endif
+      sid = 0;
+    }
+
+    std::string text = _text;
+    if (config_.model.debug) {
+#if __OHOS__
+      SHERPA_ONNX_LOGE("Raw text: %{public}s", text.c_str());
+#else
+      SHERPA_ONNX_LOGE("Raw text: %s", text.c_str());
+#endif
+    }
+
+    if (!tn_list_.empty()) {
+      for (const auto &tn : tn_list_) {
+        text = tn->Normalize(text);
+        if (config_.model.debug) {
+#if __OHOS__
+          SHERPA_ONNX_LOGE("After normalizing: %{public}s", text.c_str());
+#else
+          SHERPA_ONNX_LOGE("After normalizing: %s", text.c_str());
+#endif
+        }
+      }
+    }
+
+    std::vector<TokenIDs> token_ids =
+        frontend_->ConvertTextToTokenIds(text, "en-us");
+
+    if (token_ids.empty() ||
+        (token_ids.size() == 1 && token_ids[0].tokens.empty())) {
+#if __OHOS__
+      SHERPA_ONNX_LOGE("Failed to convert '%{public}s' to token IDs",
+                       text.c_str());
+#else
+      SHERPA_ONNX_LOGE("Failed to convert '%s' to token IDs", text.c_str());
+#endif
+      return {};
+    }
+
+    std::vector<std::vector<int64_t>> x;
+
+    x.reserve(token_ids.size());
+
+    for (auto &i : token_ids) {
+      x.push_back(std::move(i.tokens));
+    }
+
+    int32_t x_size = static_cast<int32_t>(x.size());
+
+    if (config_.max_num_sentences != 1) {
+#if __OHOS__
+      SHERPA_ONNX_LOGE(
+          "max_num_sentences (%{public}d) != 1 is ignored for Kokoro TTS "
+          "models",
+          config_.max_num_sentences);
+#else
+      SHERPA_ONNX_LOGE(
+          "max_num_sentences (%d) != 1 is ignored for Kokoro TTS models",
+          config_.max_num_sentences);
+#endif
+    }
+
+    // the input text is too long, we process sentences within it in batches
+    // to avoid OOM. Batch size is config_.max_num_sentences
+    std::vector<std::vector<int64_t>> batch_x;
+
+    int32_t batch_size = 1;
+    batch_x.reserve(config_.max_num_sentences);
+    int32_t num_batches = x_size / batch_size;
+
+    if (config_.model.debug) {
+#if __OHOS__
+      SHERPA_ONNX_LOGE(
+          "Split it into %{public}d batches. batch size: "
+          "%{public}d. Number of sentences: %{public}d",
+          num_batches, batch_size, x_size);
+#else
+      SHERPA_ONNX_LOGE(
+          "Split it into %d batches. batch size: %d. Number "
+          "of sentences: %d",
+          num_batches, batch_size, x_size);
+#endif
+    }
+
+    GeneratedAudio ans;
+
+    int32_t should_continue = 1;
+
+    int32_t k = 0;
+
+    for (int32_t b = 0; b != num_batches && should_continue; ++b) {
+      batch_x.clear();
+      for (int32_t i = 0; i != batch_size; ++i, ++k) {
+        batch_x.push_back(std::move(x[k]));
+      }
+
+      auto audio = Process(batch_x, sid, speed);
+      ans.sample_rate = audio.sample_rate;
+      ans.samples.insert(ans.samples.end(), audio.samples.begin(),
+                         audio.samples.end());
+      if (callback) {
+        should_continue = callback(audio.samples.data(), audio.samples.size(),
+                                   (b + 1) * 1.0 / num_batches);
+        // Caution(fangjun): audio is freed when the callback returns, so users
+        // should copy the data if they want to access the data after
+        // the callback returns to avoid segmentation fault.
+      }
+    }
+
+    batch_x.clear();
+    while (k < static_cast<int32_t>(x.size()) && should_continue) {
+      batch_x.push_back(std::move(x[k]));
+
+      ++k;
+    }
+
+    if (!batch_x.empty()) {
+      auto audio = Process(batch_x, sid, speed);
+      ans.sample_rate = audio.sample_rate;
+      ans.samples.insert(ans.samples.end(), audio.samples.begin(),
+                         audio.samples.end());
+      if (callback) {
+        callback(audio.samples.data(), audio.samples.size(), 1.0);
+        // Caution(fangjun): audio is freed when the callback returns, so users
+        // should copy the data if they want to access the data after
+        // the callback returns to avoid segmentation fault.
+      }
+    }
+
+    return ans;
+  }
+
+ private:
+  template <typename Manager>
+  void InitFrontend(Manager *mgr) {
+    const auto &meta_data = model_->GetMetaData();
+    frontend_ = std::make_unique<PiperPhonemizeLexicon>(
+        mgr, config_.model.kokoro.tokens, config_.model.kokoro.data_dir,
+        meta_data);
+  }
+
+  void InitFrontend() {
+    const auto &meta_data = model_->GetMetaData();
+
+    frontend_ = std::make_unique<PiperPhonemizeLexicon>(
+        config_.model.kokoro.tokens, config_.model.kokoro.data_dir, meta_data);
+  }
+
+  GeneratedAudio Process(const std::vector<std::vector<int64_t>> &tokens,
+                         int32_t sid, float speed) const {
+    int32_t num_tokens = 0;
+    for (const auto &k : tokens) {
+      num_tokens += k.size();
+    }
+
+    std::vector<int64_t> x;
+    x.reserve(num_tokens);
+    for (const auto &k : tokens) {
+      x.insert(x.end(), k.begin(), k.end());
+    }
+
+    auto memory_info =
+        Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
+
+    std::array<int64_t, 2> x_shape = {1, static_cast<int32_t>(x.size())};
+    Ort::Value x_tensor = Ort::Value::CreateTensor(
+        memory_info, x.data(), x.size(), x_shape.data(), x_shape.size());
+
+    Ort::Value audio = model_->Run(std::move(x_tensor), sid, speed);
+
+    std::vector<int64_t> audio_shape =
+        audio.GetTensorTypeAndShapeInfo().GetShape();
+
+    int64_t total = 1;
+    // The output shape may be (1, 1, total) or (1, total) or (total,)
+    for (auto i : audio_shape) {
+      total *= i;
+    }
+
+    const float *p = audio.GetTensorData<float>();
+
+    GeneratedAudio ans;
+    ans.sample_rate = model_->GetMetaData().sample_rate;
+    ans.samples = std::vector<float>(p, p + total);
+    return ans;
+  }
+
+ private:
+  OfflineTtsConfig config_;
+  std::unique_ptr<OfflineTtsKokoroModel> model_;
+  std::vector<std::unique_ptr<kaldifst::TextNormalizer>> tn_list_;
+  std::unique_ptr<OfflineTtsFrontend> frontend_;
+};
+
+}  // namespace sherpa_onnx
+#endif  // SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_IMPL_H_
--- a/sherpa-onnx/csrc/offline-tts-kokoro-model-config.cc 0 → 100644
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-kokoro-model-config.cc 0 → 100644
查看文件 @ffc6b48
+// sherpa-onnx/csrc/offline-tts-kokoro-model-config.cc
+//
+// Copyright (c)  2025  Xiaomi Corporation
+
+#include "sherpa-onnx/csrc/offline-tts-kokoro-model-config.h"
+
+#include <vector>
+
+#include "sherpa-onnx/csrc/file-utils.h"
+#include "sherpa-onnx/csrc/macros.h"
+
+namespace sherpa_onnx {
+
+void OfflineTtsKokoroModelConfig::Register(ParseOptions *po) {
+  po->Register("kokoro-model", &model, "Path to Kokoro model");
+  po->Register("kokoro-voices", &voices,
+               "Path to voices.bin for Kokoro models");
+  po->Register("kokoro-tokens", &tokens,
+               "Path to tokens.txt for Kokoro models");
+  po->Register("kokoro-data-dir", &data_dir,
+               "Path to the directory containing dict for espeak-ng.");
+  po->Register("kokoro-length-scale", &length_scale,
+               "Speech speed. Larger->Slower; Smaller->faster.");
+}
+
+bool OfflineTtsKokoroModelConfig::Validate() const {
+  if (model.empty()) {
+    SHERPA_ONNX_LOGE("Please provide --kokoro-model");
+    return false;
+  }
+
+  if (!FileExists(model)) {
+    SHERPA_ONNX_LOGE("--kokoro-model: '%s' does not exist", model.c_str());
+    return false;
+  }
+
+  if (tokens.empty()) {
+    SHERPA_ONNX_LOGE("Please provide --kokoro-tokens");
+    return false;
+  }
+
+  if (!FileExists(tokens)) {
+    SHERPA_ONNX_LOGE("--kokoro-tokens: '%s' does not exist", tokens.c_str());
+    return false;
+  }
+
+  if (data_dir.empty()) {
+    SHERPA_ONNX_LOGE("Please provide --kokoro-data-dir");
+    return false;
+  }
+
+  if (!FileExists(data_dir + "/phontab")) {
+    SHERPA_ONNX_LOGE(
+        "'%s/phontab' does not exist. Please check --kokoro-data-dir",
+        data_dir.c_str());
+    return false;
+  }
+
+  if (!FileExists(data_dir + "/phonindex")) {
+    SHERPA_ONNX_LOGE(
+        "'%s/phonindex' does not exist. Please check --kokoro-data-dir",
+        data_dir.c_str());
+    return false;
+  }
+
+  if (!FileExists(data_dir + "/phondata")) {
+    SHERPA_ONNX_LOGE(
+        "'%s/phondata' does not exist. Please check --kokoro-data-dir",
+        data_dir.c_str());
+    return false;
+  }
+
+  if (!FileExists(data_dir + "/intonations")) {
+    SHERPA_ONNX_LOGE(
+        "'%s/intonations' does not exist. Please check --kokoro-data-dir",
+        data_dir.c_str());
+    return false;
+  }
+
+  return true;
+}
+
+std::string OfflineTtsKokoroModelConfig::ToString() const {
+  std::ostringstream os;
+
+  os << "OfflineTtsKokoroModelConfig(";
+  os << "model=\"" << model << "\", ";
+  os << "voices=\"" << voices << "\", ";
+  os << "tokens=\"" << tokens << "\", ";
+  os << "data_dir=\"" << data_dir << "\", ";
+  os << "length_scale=" << length_scale << ")";
+
+  return os.str();
+}
+
+}  // namespace sherpa_onnx
--- a/sherpa-onnx/csrc/offline-tts-kokoro-model-config.h 0 → 100644
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-kokoro-model-config.h 0 → 100644
查看文件 @ffc6b48
+// sherpa-onnx/csrc/offline-tts-kokoro-model-config.h
+//
+// Copyright (c)  2025  Xiaomi Corporation
+
+#ifndef SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_MODEL_CONFIG_H_
+#define SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_MODEL_CONFIG_H_
+
+#include <string>
+
+#include "sherpa-onnx/csrc/parse-options.h"
+
+namespace sherpa_onnx {
+
+struct OfflineTtsKokoroModelConfig {
+  std::string model;
+  std::string voices;
+  std::string tokens;
+
+  std::string data_dir;
+
+  // speed = 1 / length_scale
+  float length_scale = 1.0;
+
+  OfflineTtsKokoroModelConfig() = default;
+
+  OfflineTtsKokoroModelConfig(const std::string &model,
+                              const std::string &voices,
+                              const std::string &tokens,
+                              const std::string &data_dir, float length_scale)
+      : model(model),
+        voices(voices),
+        tokens(tokens),
+        data_dir(data_dir),
+        length_scale(length_scale) {}
+
+  void Register(ParseOptions *po);
+  bool Validate() const;
+
+  std::string ToString() const;
+};
+
+}  // namespace sherpa_onnx
+
+#endif  // SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_MODEL_CONFIG_H_
--- a/sherpa-onnx/csrc/offline-tts-kokoro-model-meta-data.h 0 → 100644
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-kokoro-model-meta-data.h 0 → 100644
查看文件 @ffc6b48
+// sherpa-onnx/csrc/offline-tts-kokoro-model-metadata.h
+//
+// Copyright (c)  2025  Xiaomi Corporation
+
+#ifndef SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_MODEL_META_DATA_H_
+#define SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_MODEL_META_DATA_H_
+
+#include <cstdint>
+#include <string>
+
+namespace sherpa_onnx {
+
+// please refer to
+// https://github.com/k2-fsa/sherpa-onnx/blob/master/scripts/kokoro/add-meta-data.py
+struct OfflineTtsKokoroModelMetaData {
+  int32_t sample_rate = 0;
+  int32_t num_speakers = 0;
+  int32_t version = 1;
+  int32_t has_espeak = 1;
+  int32_t max_token_len = 0;
+};
+
+}  // namespace sherpa_onnx
+
+#endif  // SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_MODEL_META_DATA_H_
--- a/sherpa-onnx/csrc/offline-tts-kokoro-model.cc 0 → 100644
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-kokoro-model.cc 0 → 100644
查看文件 @ffc6b48
+// sherpa-onnx/csrc/offline-tts-kokoro-model.cc
+//
+// Copyright (c)  2025  Xiaomi Corporation
+
+#include "sherpa-onnx/csrc/offline-tts-kokoro-model.h"
+
+#include <algorithm>
+#include <string>
+#include <utility>
+#include <vector>
+
+#if __ANDROID_API__ >= 9
+#include "android/asset_manager.h"
+#include "android/asset_manager_jni.h"
+#endif
+
+#if __OHOS__
+#include "rawfile/raw_file_manager.h"
+#endif
+
+#include "sherpa-onnx/csrc/macros.h"
+#include "sherpa-onnx/csrc/onnx-utils.h"
+#include "sherpa-onnx/csrc/session.h"
+#include "sherpa-onnx/csrc/text-utils.h"
+
+namespace sherpa_onnx {
+
+class OfflineTtsKokoroModel::Impl {
+ public:
+  explicit Impl(const OfflineTtsModelConfig &config)
+      : config_(config),
+        env_(ORT_LOGGING_LEVEL_ERROR),
+        sess_opts_(GetSessionOptions(config)),
+        allocator_{} {
+    auto model_buf = ReadFile(config.kokoro.model);
+    auto voices_buf = ReadFile(config.kokoro.voices);
+    Init(model_buf.data(), model_buf.size(), voices_buf.data(),
+         voices_buf.size());
+  }
+
+  template <typename Manager>
+  Impl(Manager *mgr, const OfflineTtsModelConfig &config)
+      : config_(config),
+        env_(ORT_LOGGING_LEVEL_ERROR),
+        sess_opts_(GetSessionOptions(config)),
+        allocator_{} {
+    auto model_buf = ReadFile(mgr, config.kokoro.model);
+    auto voices_buf = ReadFile(mgr, config.kokoro.voices);
+    Init(model_buf.data(), model_buf.size(), voices_buf.data(),
+         voices_buf.size());
+  }
+
+  const OfflineTtsKokoroModelMetaData &GetMetaData() const {
+    return meta_data_;
+  }
+
+  Ort::Value Run(Ort::Value x, int32_t sid, float speed) {
+    auto memory_info =
+        Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
+
+    std::vector<int64_t> x_shape = x.GetTensorTypeAndShapeInfo().GetShape();
+    if (x_shape[0] != 1) {
+      SHERPA_ONNX_LOGE("Support only batch_size == 1. Given: %d",
+                       static_cast<int32_t>(x_shape[0]));
+      exit(-1);
+    }
+
+    // there is a 0 at the front and end of x
+    int32_t len = static_cast<int32_t>(x_shape[1]) - 2;
+    int32_t num_speakers = meta_data_.num_speakers;
+    int32_t dim0 = style_dim_[0];
+    int32_t dim1 = style_dim_[2];
+    if (len >= dim0) {
+      SHERPA_ONNX_LOGE("Bad things happened! %d vs %d", len, dim0);
+      SHERPA_ONNX_EXIT(-1);
+    }
+
+    /*const*/ float *p = styles_.data() + sid * dim0 * dim1 + len * dim1;
+
+    std::array<int64_t, 2> style_embedding_shape = {1, dim1};
+    Ort::Value style_embedding = Ort::Value::CreateTensor(
+        memory_info, p, dim1, style_embedding_shape.data(),
+        style_embedding_shape.size());
+
+    int64_t speed_shape = 1;
+
+    Ort::Value speed_tensor =
+        Ort::Value::CreateTensor(memory_info, &speed, 1, &speed_shape, 1);
+
+    std::array<Ort::Value, 3> inputs = {
+        std::move(x), std::move(style_embedding), std::move(speed_tensor)};
+
+    auto out =
+        sess_->Run({}, input_names_ptr_.data(), inputs.data(), inputs.size(),
+                   output_names_ptr_.data(), output_names_ptr_.size());
+
+    return std::move(out[0]);
+  }
+
+ private:
+  void Init(void *model_data, size_t model_data_length, const char *voices_data,
+            size_t voices_data_length) {
+    sess_ = std::make_unique<Ort::Session>(env_, model_data, model_data_length,
+                                           sess_opts_);
+
+    GetInputNames(sess_.get(), &input_names_, &input_names_ptr_);
+
+    GetOutputNames(sess_.get(), &output_names_, &output_names_ptr_);
+    // get meta data
+    Ort::ModelMetadata meta_data = sess_->GetModelMetadata();
+    if (config_.debug) {
+      std::ostringstream os;
+      os << "---kokoro model---\n";
+      PrintModelMetadata(os, meta_data);
+
+      os << "----------input names----------\n";
+      int32_t i = 0;
+      for (const auto &s : input_names_) {
+        os << i << " " << s << "\n";
+        ++i;
+      }
+      os << "----------output names----------\n";
+      i = 0;
+      for (const auto &s : output_names_) {
+        os << i << " " << s << "\n";
+        ++i;
+      }
+
+#if __OHOS__
+      SHERPA_ONNX_LOGE("%{public}s\n", os.str().c_str());
+#else
+      SHERPA_ONNX_LOGE("%s\n", os.str().c_str());
+#endif
+    }
+
+    Ort::AllocatorWithDefaultOptions allocator;  // used in the macro below
+    SHERPA_ONNX_READ_META_DATA(meta_data_.sample_rate, "sample_rate");
+    SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(meta_data_.version, "version", 1);
+    SHERPA_ONNX_READ_META_DATA(meta_data_.num_speakers, "n_speakers");
+    SHERPA_ONNX_READ_META_DATA(meta_data_.has_espeak, "has_espeak");
+
+    if (config_.debug) {
+      std::vector<std::string> speaker_names;
+      SHERPA_ONNX_READ_META_DATA_VEC_STRING(speaker_names, "speaker_names");
+      std::ostringstream os;
+      os << "\n";
+      for (int32_t i = 0; i != speaker_names.size(); ++i) {
+        os << i << "->" << speaker_names[i] << ", ";
+      }
+      os << "\n";
+
+#if __OHOS__
+      SHERPA_ONNX_LOGE("%{public}s\n", os.str().c_str());
+#else
+      SHERPA_ONNX_LOGE("%s\n", os.str().c_str());
+#endif
+    }
+
+    SHERPA_ONNX_READ_META_DATA_VEC(style_dim_, "style_dim");
+    if (style_dim_.size() != 3) {
+      SHERPA_ONNX_LOGE("style_dim should be 3-d, given: %d",
+                       static_cast<int32_t>(style_dim_.size()));
+      SHERPA_ONNX_EXIT(-1);
+    }
+
+    if (style_dim_[1] != 1) {
+      SHERPA_ONNX_LOGE("style_dim[0] should be 1, given: %d", style_dim_[1]);
+      SHERPA_ONNX_EXIT(-1);
+    }
+
+    int32_t actual_num_floats = voices_data_length / sizeof(float);
+    int32_t expected_num_floats =
+        style_dim_[0] * style_dim_[2] * meta_data_.num_speakers;
+
+    if (actual_num_floats != expected_num_floats) {
+#if __OHOS__
+      SHERPA_ONNX_LOGE(
+          "Corrupted --kokoro-voices '%{public}s'. Expected #floats: "
+          "%{public}d, actual: %{public}d",
+          config_.kokoro.voices.c_str(), expected_num_floats,
+          actual_num_floats);
+#else
+      SHERPA_ONNX_LOGE(
+          "Corrupted --kokoro-voices '%s'. Expected #floats: %d, actual: %d",
+          config_.kokoro.voices.c_str(), expected_num_floats,
+          actual_num_floats);
+#endif
+
+      SHERPA_ONNX_EXIT(-1);
+    }
+
+    styles_ = std::vector<float>(
+        reinterpret_cast<const float *>(voices_data),
+        reinterpret_cast<const float *>(voices_data) + expected_num_floats);
+
+    meta_data_.max_token_len = style_dim_[0];
+  }
+
+ private:
+  OfflineTtsModelConfig config_;
+  Ort::Env env_;
+  Ort::SessionOptions sess_opts_;
+  Ort::AllocatorWithDefaultOptions allocator_;
+
+  std::unique_ptr<Ort::Session> sess_;
+
+  std::vector<std::string> input_names_;
+  std::vector<const char *> input_names_ptr_;
+
+  std::vector<std::string> output_names_;
+  std::vector<const char *> output_names_ptr_;
+
+  OfflineTtsKokoroModelMetaData meta_data_;
+  std::vector<int32_t> style_dim_;
+
+  // (num_speakers, style_dim_[0], style_dim_[2])
+  std::vector<float> styles_;
+};
+
+OfflineTtsKokoroModel::OfflineTtsKokoroModel(
+    const OfflineTtsModelConfig &config)
+    : impl_(std::make_unique<Impl>(config)) {}
+
+template <typename Manager>
+OfflineTtsKokoroModel::OfflineTtsKokoroModel(
+    Manager *mgr, const OfflineTtsModelConfig &config)
+    : impl_(std::make_unique<Impl>(mgr, config)) {}
+
+OfflineTtsKokoroModel::~OfflineTtsKokoroModel() = default;
+
+const OfflineTtsKokoroModelMetaData &OfflineTtsKokoroModel::GetMetaData()
+    const {
+  return impl_->GetMetaData();
+}
+
+Ort::Value OfflineTtsKokoroModel::Run(Ort::Value x, int64_t sid /*= 0*/,
+                                      float speed /*= 1.0*/) const {
+  return impl_->Run(std::move(x), sid, speed);
+}
+
+#if __ANDROID_API__ >= 9
+template OfflineTtsKokoroModel::OfflineTtsKokoroModel(
+    AAssetManager *mgr, const OfflineTtsModelConfig &config);
+#endif
+
+#if __OHOS__
+template OfflineTtsKokoroModel::OfflineTtsKokoroModel(
+    NativeResourceManager *mgr, const OfflineTtsModelConfig &config);
+#endif
+
+}  // namespace sherpa_onnx
--- a/sherpa-onnx/csrc/offline-tts-kokoro-model.h 0 → 100644
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-kokoro-model.h 0 → 100644
查看文件 @ffc6b48
+// sherpa-onnx/csrc/offline-tts-kokoro-model.h
+//
+// Copyright (c)  2025  Xiaomi Corporation
+
+#ifndef SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_MODEL_H_
+#define SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_MODEL_H_
+
+#include <memory>
+#include <string>
+
+#include "onnxruntime_cxx_api.h"  // NOLINT
+#include "sherpa-onnx/csrc/offline-tts-kokoro-model-meta-data.h"
+#include "sherpa-onnx/csrc/offline-tts-model-config.h"
+
+namespace sherpa_onnx {
+
+class OfflineTtsKokoroModel {
+ public:
+  ~OfflineTtsKokoroModel();
+
+  explicit OfflineTtsKokoroModel(const OfflineTtsModelConfig &config);
+
+  template <typename Manager>
+  OfflineTtsKokoroModel(Manager *mgr, const OfflineTtsModelConfig &config);
+
+  // Return a float32 tensor containing the mel
+  // of shape (batch_size, mel_dim, num_frames)
+  Ort::Value Run(Ort::Value x, int64_t sid = 0, float speed = 1.0) const;
+
+  const OfflineTtsKokoroModelMetaData &GetMetaData() const;
+
+ private:
+  class Impl;
+  std::unique_ptr<Impl> impl_;
+};
+
+}  // namespace sherpa_onnx
+
+#endif  // SHERPA_ONNX_CSRC_OFFLINE_TTS_KOKORO_MODEL_H_
--- a/sherpa-onnx/csrc/offline-tts-matcha-model-metadata.h → sherpa-onnx/csrc/offline-tts-matcha-model-meta-data.h
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-matcha-model-metadata.h → sherpa-onnx/csrc/offline-tts-matcha-model-meta-data.h
查看文件 @ffc6b48
-// sherpa-onnx/csrc/offline-tts-matcha-model-metadata.h
+// sherpa-onnx/csrc/offline-tts-matcha-model-meta-data.h
 //
 // Copyright (c)  2023  Xiaomi Corporation
-#ifndef SHERPA_ONNX_CSRC_OFFLINE_TTS_MATCHA_MODEL_METADATA_H_
-#define SHERPA_ONNX_CSRC_OFFLINE_TTS_MATCHA_MODEL_METADATA_H_
+#ifndef SHERPA_ONNX_CSRC_OFFLINE_TTS_MATCHA_MODEL_META_DATA_H_
+#define SHERPA_ONNX_CSRC_OFFLINE_TTS_MATCHA_MODEL_META_DATA_H_
 #include <cstdint>
 #include <string>
@@ -25,4 +25,4 @@ struct OfflineTtsMatchaModelMetaData {
 }  // namespace sherpa_onnx
-#endif  // SHERPA_ONNX_CSRC_OFFLINE_TTS_MATCHA_MODEL_METADATA_H_
+#endif  // SHERPA_ONNX_CSRC_OFFLINE_TTS_MATCHA_MODEL_META_DATA_H_
--- a/sherpa-onnx/csrc/offline-tts-matcha-model.h
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-matcha-model.h
查看文件 @ffc6b48
@@ -9,7 +9,7 @@
 #include <string>
 #include "onnxruntime_cxx_api.h"  // NOLINT
-#include "sherpa-onnx/csrc/offline-tts-matcha-model-metadata.h"
+#include "sherpa-onnx/csrc/offline-tts-matcha-model-meta-data.h"
 #include "sherpa-onnx/csrc/offline-tts-model-config.h"
 namespace sherpa_onnx {
--- a/sherpa-onnx/csrc/offline-tts-model-config.cc
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-model-config.cc
查看文件 @ffc6b48
@@ -11,6 +11,7 @@ namespace sherpa_onnx {
 void OfflineTtsModelConfig::Register(ParseOptions *po) {
   vits.Register(po);
   matcha.Register(po);
+  kokoro.Register(po);
   po->Register("num-threads", &num_threads,
                "Number of threads to run the neural network");
@@ -32,7 +33,11 @@ bool OfflineTtsModelConfig::Validate() const {
     return vits.Validate();
   }
-  return matcha.Validate();
+  if (!matcha.acoustic_model.empty()) {
+    return matcha.Validate();
+  }
+
+  return kokoro.Validate();
 }
 std::string OfflineTtsModelConfig::ToString() const {
@@ -41,6 +46,7 @@ std::string OfflineTtsModelConfig::ToString() const {
   os << "OfflineTtsModelConfig(";
   os << "vits=" << vits.ToString() << ", ";
   os << "matcha=" << matcha.ToString() << ", ";
+  os << "kokoro=" << kokoro.ToString() << ", ";
   os << "num_threads=" << num_threads << ", ";
   os << "debug=" << (debug ? "True" : "False") << ", ";
   os << "provider=\"" << provider << "\")";
--- a/sherpa-onnx/csrc/offline-tts-model-config.h
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-model-config.h
查看文件 @ffc6b48
@@ -7,6 +7,7 @@
 #include <string>
+#include "sherpa-onnx/csrc/offline-tts-kokoro-model-config.h"
 #include "sherpa-onnx/csrc/offline-tts-matcha-model-config.h"
 #include "sherpa-onnx/csrc/offline-tts-vits-model-config.h"
 #include "sherpa-onnx/csrc/parse-options.h"
@@ -16,6 +17,7 @@ namespace sherpa_onnx {
 struct OfflineTtsModelConfig {
   OfflineTtsVitsModelConfig vits;
   OfflineTtsMatchaModelConfig matcha;
+  OfflineTtsKokoroModelConfig kokoro;
   int32_t num_threads = 1;
   bool debug = false;
@@ -25,10 +27,12 @@ struct OfflineTtsModelConfig {
   OfflineTtsModelConfig(const OfflineTtsVitsModelConfig &vits,
                         const OfflineTtsMatchaModelConfig &matcha,
+                        const OfflineTtsKokoroModelConfig &kokoro,
                         int32_t num_threads, bool debug,
                         const std::string &provider)
       : vits(vits),
         matcha(matcha),
+        kokoro(kokoro),
         num_threads(num_threads),
         debug(debug),
         provider(provider) {}
--- a/sherpa-onnx/csrc/offline-tts-vits-model-metadata.h → sherpa-onnx/csrc/offline-tts-vits-model-meta-data.h
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-vits-model-metadata.h → sherpa-onnx/csrc/offline-tts-vits-model-meta-data.h
查看文件 @ffc6b48
-// sherpa-onnx/csrc/offline-tts-vits-model-metadata.h
+// sherpa-onnx/csrc/offline-tts-vits-model-meta-data.h
 //
 // Copyright (c)  2023  Xiaomi Corporation
-#ifndef SHERPA_ONNX_CSRC_OFFLINE_TTS_VITS_MODEL_METADATA_H_
-#define SHERPA_ONNX_CSRC_OFFLINE_TTS_VITS_MODEL_METADATA_H_
+#ifndef SHERPA_ONNX_CSRC_OFFLINE_TTS_VITS_MODEL_META_DATA_H_
+#define SHERPA_ONNX_CSRC_OFFLINE_TTS_VITS_MODEL_META_DATA_H_
 #include <cstdint>
 #include <string>
@@ -46,4 +46,4 @@ struct OfflineTtsVitsModelMetaData {
 }  // namespace sherpa_onnx
-#endif  // SHERPA_ONNX_CSRC_OFFLINE_TTS_VITS_MODEL_METADATA_H_
+#endif  // SHERPA_ONNX_CSRC_OFFLINE_TTS_VITS_MODEL_META_DATA_H_
--- a/sherpa-onnx/csrc/offline-tts-vits-model.h
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/offline-tts-vits-model.h
查看文件 @ffc6b48
@@ -10,7 +10,7 @@
 #include "onnxruntime_cxx_api.h"  // NOLINT
 #include "sherpa-onnx/csrc/offline-tts-model-config.h"
-#include "sherpa-onnx/csrc/offline-tts-vits-model-metadata.h"
+#include "sherpa-onnx/csrc/offline-tts-vits-model-meta-data.h"
 namespace sherpa_onnx {
--- a/sherpa-onnx/csrc/piper-phonemize-lexicon.cc
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/piper-phonemize-lexicon.cc
查看文件 @ffc6b48
@@ -155,6 +155,36 @@ static std::vector<int64_t> PiperPhonemesToIdsMatcha(
   return ans;
 }
+static std::vector<std::vector<int64_t>> PiperPhonemesToIdsKokoro(
+    const std::unordered_map<char32_t, int32_t> &token2id,
+    const std::vector<piper::Phoneme> &phonemes, int32_t max_len) {
+  std::vector<std::vector<int64_t>> ans;
+
+  std::vector<int64_t> current;
+  current.reserve(phonemes.size());
+
+  for (auto p : phonemes) {
+    if (token2id.count(p)) {
+      if (current.size() > max_len - 1) {
+        current.push_back(0);
+        ans.push_back(std::move(current));
+
+        current.reserve(phonemes.size());
+        current.push_back(0);
+      }
+
+      current.push_back(token2id.at(p));
+    } else {
+      SHERPA_ONNX_LOGE("Skip unknown phonemes. Unicode codepoint: \\U+%04x.",
+                       static_cast<uint32_t>(p));
+    }
+  }
+
+  current.push_back(0);
+  ans.push_back(std::move(current));
+  return ans;
+}
+
 static std::vector<int64_t> CoquiPhonemesToIds(
     const std::unordered_map<char32_t, int32_t> &token2id,
     const std::vector<piper::Phoneme> &phonemes,
@@ -269,6 +299,18 @@ PiperPhonemizeLexicon::PiperPhonemizeLexicon(
   InitEspeak(data_dir);
 }
+PiperPhonemizeLexicon::PiperPhonemizeLexicon(
+    const std::string &tokens, const std::string &data_dir,
+    const OfflineTtsKokoroModelMetaData &kokoro_meta_data)
+    : kokoro_meta_data_(kokoro_meta_data), is_kokoro_(true) {
+  {
+    std::ifstream is(tokens);
+    token2id_ = ReadTokens(is);
+  }
+
+  InitEspeak(data_dir);
+}
+
 template <typename Manager>
 PiperPhonemizeLexicon::PiperPhonemizeLexicon(
     Manager *mgr, const std::string &tokens, const std::string &data_dir,
@@ -286,10 +328,29 @@ PiperPhonemizeLexicon::PiperPhonemizeLexicon(
   InitEspeak(data_dir);
 }
+template <typename Manager>
+PiperPhonemizeLexicon::PiperPhonemizeLexicon(
+    Manager *mgr, const std::string &tokens, const std::string &data_dir,
+    const OfflineTtsKokoroModelMetaData &kokoro_meta_data)
+    : kokoro_meta_data_(kokoro_meta_data), is_kokoro_(true) {
+  {
+    auto buf = ReadFile(mgr, tokens);
+    std::istrstream is(buf.data(), buf.size());
+    token2id_ = ReadTokens(is);
+  }
+
+  // We should copy the directory of espeak-ng-data from the asset to
+  // some internal or external storage and then pass the directory to
+  // data_dir.
+  InitEspeak(data_dir);
+}
+
 std::vector<TokenIDs> PiperPhonemizeLexicon::ConvertTextToTokenIds(
     const std::string &text, const std::string &voice /*= ""*/) const {
   if (is_matcha_) {
     return ConvertTextToTokenIdsMatcha(text, voice);
+  } else if (is_kokoro_) {
+    return ConvertTextToTokenIdsKokoro(text, voice);
   } else {
     return ConvertTextToTokenIdsVits(text, voice);
   }
@@ -320,6 +381,32 @@ std::vector<TokenIDs> PiperPhonemizeLexicon::ConvertTextToTokenIdsMatcha(
   return ans;
 }
+std::vector<TokenIDs> PiperPhonemizeLexicon::ConvertTextToTokenIdsKokoro(
+    const std::string &text, const std::string &voice /*= ""*/) const {
+  piper::eSpeakPhonemeConfig config;
+
+  // ./bin/espeak-ng-bin --path  ./install/share/espeak-ng-data/ --voices
+  // to list available voices
+  config.voice = voice;  // e.g., voice is en-us
+
+  std::vector<std::vector<piper::Phoneme>> phonemes;
+
+  CallPhonemizeEspeak(text, config, &phonemes);
+
+  std::vector<TokenIDs> ans;
+
+  for (const auto &p : phonemes) {
+    auto phoneme_ids =
+        PiperPhonemesToIdsKokoro(token2id_, p, kokoro_meta_data_.max_token_len);
+
+    for (auto &ids : phoneme_ids) {
+      ans.emplace_back(std::move(ids));
+    }
+  }
+
+  return ans;
+}
+
 std::vector<TokenIDs> PiperPhonemizeLexicon::ConvertTextToTokenIdsVits(
     const std::string &text, const std::string &voice /*= ""*/) const {
   piper::eSpeakPhonemeConfig config;
@@ -363,6 +450,10 @@ template PiperPhonemizeLexicon::PiperPhonemizeLexicon(
 template PiperPhonemizeLexicon::PiperPhonemizeLexicon(
     AAssetManager *mgr, const std::string &tokens, const std::string &data_dir,
     const OfflineTtsMatchaModelMetaData &matcha_meta_data);
+
+template PiperPhonemizeLexicon::PiperPhonemizeLexicon(
+    AAssetManager *mgr, const std::string &tokens, const std::string &data_dir,
+    const OfflineTtsKokoroModelMetaData &kokoro_meta_data);
 #endif
 #if __OHOS__
@@ -375,6 +466,11 @@ template PiperPhonemizeLexicon::PiperPhonemizeLexicon(
     NativeResourceManager *mgr, const std::string &tokens,
     const std::string &data_dir,
     const OfflineTtsMatchaModelMetaData &matcha_meta_data);
+
+template PiperPhonemizeLexicon::PiperPhonemizeLexicon(
+    NativeResourceManager *mgr, const std::string &tokens,
+    const std::string &data_dir,
+    const OfflineTtsKokoroModelMetaData &kokoro_meta_data);
 #endif
 }  // namespace sherpa_onnx
--- a/sherpa-onnx/csrc/piper-phonemize-lexicon.h
查看文件 @ffc6b48
+++ b/sherpa-onnx/csrc/piper-phonemize-lexicon.h
查看文件 @ffc6b48
@@ -10,8 +10,9 @@
 #include <vector>
 #include "sherpa-onnx/csrc/offline-tts-frontend.h"
-#include "sherpa-onnx/csrc/offline-tts-matcha-model-metadata.h"
-#include "sherpa-onnx/csrc/offline-tts-vits-model-metadata.h"
+#include "sherpa-onnx/csrc/offline-tts-kokoro-model-meta-data.h"
+#include "sherpa-onnx/csrc/offline-tts-matcha-model-meta-data.h"
+#include "sherpa-onnx/csrc/offline-tts-vits-model-meta-data.h"
 namespace sherpa_onnx {
@@ -23,6 +24,9 @@ class PiperPhonemizeLexicon : public OfflineTtsFrontend {
   PiperPhonemizeLexicon(const std::string &tokens, const std::string &data_dir,
                         const OfflineTtsMatchaModelMetaData &matcha_meta_data);
+  PiperPhonemizeLexicon(const std::string &tokens, const std::string &data_dir,
+                        const OfflineTtsKokoroModelMetaData &kokoro_meta_data);
+
   template <typename Manager>
   PiperPhonemizeLexicon(Manager *mgr, const std::string &tokens,
                         const std::string &data_dir,
@@ -33,6 +37,11 @@ class PiperPhonemizeLexicon : public OfflineTtsFrontend {
                         const std::string &data_dir,
                         const OfflineTtsMatchaModelMetaData &matcha_meta_data);
+  template <typename Manager>
+  PiperPhonemizeLexicon(Manager *mgr, const std::string &tokens,
+                        const std::string &data_dir,
+                        const OfflineTtsKokoroModelMetaData &kokoro_meta_data);
+
   std::vector<TokenIDs> ConvertTextToTokenIds(
       const std::string &text, const std::string &voice = "") const override;
@@ -43,12 +52,17 @@ class PiperPhonemizeLexicon : public OfflineTtsFrontend {
   std::vector<TokenIDs> ConvertTextToTokenIdsMatcha(
       const std::string &text, const std::string &voice = "") const;
+  std::vector<TokenIDs> ConvertTextToTokenIdsKokoro(
+      const std::string &text, const std::string &voice = "") const;
+
  private:
   // map unicode codepoint to an integer ID
   std::unordered_map<char32_t, int32_t> token2id_;
   OfflineTtsVitsModelMetaData vits_meta_data_;
   OfflineTtsMatchaModelMetaData matcha_meta_data_;
+  OfflineTtsKokoroModelMetaData kokoro_meta_data_;
   bool is_matcha_ = false;
+  bool is_kokoro_ = false;
 };
 }  // namespace sherpa_onnx
--- a/sherpa-onnx/python/csrc/CMakeLists.txt
查看文件 @ffc6b48
+++ b/sherpa-onnx/python/csrc/CMakeLists.txt
查看文件 @ffc6b48
@@ -54,6 +54,7 @@ endif()
 if(SHERPA_ONNX_ENABLE_TTS)
   list(APPEND srcs
+    offline-tts-kokoro-model-config.cc
     offline-tts-matcha-model-config.cc
     offline-tts-model-config.cc
     offline-tts-vits-model-config.cc
--- a/sherpa-onnx/python/csrc/offline-tts-kokoro-model-config.cc 0 → 100644
查看文件 @ffc6b48
+++ b/sherpa-onnx/python/csrc/offline-tts-kokoro-model-config.cc 0 → 100644
查看文件 @ffc6b48
+// sherpa-onnx/python/csrc/offline-tts-kokoro-model-config.cc
+//
+// Copyright (c)  2025  Xiaomi Corporation
+
+#include "sherpa-onnx/python/csrc/offline-tts-kokoro-model-config.h"
+
+#include <string>
+
+#include "sherpa-onnx/csrc/offline-tts-kokoro-model-config.h"
+
+namespace sherpa_onnx {
+
+void PybindOfflineTtsKokoroModelConfig(py::module *m) {
+  using PyClass = OfflineTtsKokoroModelConfig;
+
+  py::class_<PyClass>(*m, "OfflineTtsKokoroModelConfig")
+      .def(py::init<>())
+      .def(py::init<const std::string &, const std::string &,
+                    const std::string &, const std::string &, float>(),
+           py::arg("model"), py::arg("voices"), py::arg("tokens"),
+           py::arg("data_dir"), py::arg("length_scale") = 1.0)
+      .def_readwrite("model", &PyClass::model)
+      .def_readwrite("voices", &PyClass::voices)
+      .def_readwrite("tokens", &PyClass::tokens)
+      .def_readwrite("data_dir", &PyClass::data_dir)
+      .def_readwrite("length_scale", &PyClass::length_scale)
+      .def("__str__", &PyClass::ToString)
+      .def("validate", &PyClass::Validate);
+}
+
+}  // namespace sherpa_onnx
--- a/sherpa-onnx/python/csrc/offline-tts-kokoro-model-config.h 0 → 100644
查看文件 @ffc6b48
+++ b/sherpa-onnx/python/csrc/offline-tts-kokoro-model-config.h 0 → 100644
查看文件 @ffc6b48
+// sherpa-onnx/python/csrc/offline-tts-kokoro-model-config.h
+//
+// Copyright (c)  2025  Xiaomi Corporation
+
+#ifndef SHERPA_ONNX_PYTHON_CSRC_OFFLINE_TTS_KOKORO_MODEL_CONFIG_H_
+#define SHERPA_ONNX_PYTHON_CSRC_OFFLINE_TTS_KOKORO_MODEL_CONFIG_H_
+
+#include "sherpa-onnx/python/csrc/sherpa-onnx.h"
+
+namespace sherpa_onnx {
+
+void PybindOfflineTtsKokoroModelConfig(py::module *m);
+
+}
+
+#endif  // SHERPA_ONNX_PYTHON_CSRC_OFFLINE_TTS_KOKORO_MODEL_CONFIG_H_
--- a/sherpa-onnx/python/csrc/offline-tts-model-config.cc
查看文件 @ffc6b48
+++ b/sherpa-onnx/python/csrc/offline-tts-model-config.cc
查看文件 @ffc6b48
@@ -7,6 +7,7 @@
 #include <string>
 #include "sherpa-onnx/csrc/offline-tts-model-config.h"
+#include "sherpa-onnx/python/csrc/offline-tts-kokoro-model-config.h"
 #include "sherpa-onnx/python/csrc/offline-tts-matcha-model-config.h"
 #include "sherpa-onnx/python/csrc/offline-tts-vits-model-config.h"
@@ -15,20 +16,24 @@ namespace sherpa_onnx {
 void PybindOfflineTtsModelConfig(py::module *m) {
   PybindOfflineTtsVitsModelConfig(m);
   PybindOfflineTtsMatchaModelConfig(m);
+  PybindOfflineTtsKokoroModelConfig(m);
   using PyClass = OfflineTtsModelConfig;
   py::class_<PyClass>(*m, "OfflineTtsModelConfig")
       .def(py::init<>())
       .def(py::init<const OfflineTtsVitsModelConfig &,
-                    const OfflineTtsMatchaModelConfig &, int32_t, bool,
+                    const OfflineTtsMatchaModelConfig &,
+                    const OfflineTtsKokoroModelConfig &, int32_t, bool,
                     const std::string &>(),
            py::arg("vits") = OfflineTtsVitsModelConfig{},
            py::arg("matcha") = OfflineTtsMatchaModelConfig{},
+           py::arg("kokoro") = OfflineTtsKokoroModelConfig{},
            py::arg("num_threads") = 1, py::arg("debug") = false,
            py::arg("provider") = "cpu")
       .def_readwrite("vits", &PyClass::vits)
       .def_readwrite("matcha", &PyClass::matcha)
+      .def_readwrite("kokoro", &PyClass::kokoro)
       .def_readwrite("num_threads", &PyClass::num_threads)
       .def_readwrite("debug", &PyClass::debug)
       .def_readwrite("provider", &PyClass::provider)
--- a/sherpa-onnx/python/sherpa_onnx/__init__.py
查看文件 @ffc6b48
+++ b/sherpa-onnx/python/sherpa_onnx/__init__.py
查看文件 @ffc6b48
@@ -20,6 +20,7 @@ from _sherpa_onnx import (
     OfflineStream,
     OfflineTts,
     OfflineTtsConfig,
+    OfflineTtsKokoroModelConfig,
     OfflineTtsMatchaModelConfig,
     OfflineTtsModelConfig,
     OfflineTtsVitsModelConfig,