mirror of
https://github.com/k2-fsa/sherpa-onnx.git
synced 2026-11-10 21:11:03 +08:00
Fangjun Kuang
0b3647632f
Fixes #3731 espeak-ng and piper-phonemize are no longer built into sherpa-onnx. Text frontends are now: - **lexicon** — built in, no extra dependency - **phonemize** — phonemize outside sherpa-onnx (e.g. [piper-phonemize](https://github.com/csukuangfj/piper-phonemize)) and pass the result in. That library is GPL, so it stays optional: sherpa-onnx is GPL-free after this PR. ## API - `SherpaOnnxGenerationConfig` gains `phoneme_codepoints` and `tokens` (mutually exclusive alternatives to `text`) - `data_dir` on the TTS model configs is deprecated and ignored; the ABI slot is kept - all bindings updated: C/C++, Python, Java, Kotlin, Go, Rust, C#, Swift, Pascal, Dart/Flutter, node-addon, WASM, HarmonyOS
80 lines
3.2 KiB
Python
Executable File
80 lines
3.2 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Test a Matcha Chinese+English TTS model using lexicon-based phonemization
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(no espeak-ng data, no external phonemizer needed).
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If you don't want to use a lexicon, please see
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test-offline-tts-matcha-zh-en-phonemize.py which uses pypinyin + piper_phonemize instead.
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Passes two lexicon files (comma-separated): the zh lexicon from the model
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directory and the en lexicon (lexicon-en-us.txt).
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Supported extra parameters in gen_config.extra (all optional):
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- min_words_in_sentence, int, default 5.
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Merge adjacent sentences if the number of words is less than this.
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Each CJK character counts as one word; English words are space-separated.
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- max_words_in_sentence, int, default 20.
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Split a sentence into chunks if the number of words exceeds this.
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Splits at punctuation or space boundaries.
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- debug, int, default from model config.
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Download model, vocoder, and lexicon:
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wget https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/matcha-icefall-zh-en.tar.bz2
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tar xf matcha-icefall-zh-en.tar.bz2
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wget https://github.com/k2-fsa/sherpa-onnx/releases/download/vocoder-models/vocos-16khz-univ.onnx
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wget https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/lexicon-en-us.txt
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"""
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import time
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import sherpa_onnx
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import soundfile as sf
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tts_config = sherpa_onnx.OfflineTtsConfig(
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model=sherpa_onnx.OfflineTtsModelConfig(
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matcha=sherpa_onnx.OfflineTtsMatchaModelConfig(
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acoustic_model="./matcha-icefall-zh-en/model-steps-3.onnx",
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vocoder="./vocos-16khz-univ.onnx",
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tokens="./matcha-icefall-zh-en/tokens.txt",
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lexicon="./matcha-icefall-zh-en/lexicon.txt,./lexicon-en-us.txt",
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),
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debug=True,
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),
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rule_fsts="./matcha-icefall-zh-en/phone-zh.fst,./matcha-icefall-zh-en/date-zh.fst,./matcha-icefall-zh-en/number-zh.fst",
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)
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tts = sherpa_onnx.OfflineTts(tts_config)
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text = (
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"我最近在学习machine learning，希望能够在未来的artificial intelligence领域有所建树。"
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"在这次vocation中，我们计划去Paris欣赏埃菲尔铁塔和卢浮宫的美景。"
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"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。"
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"开始数字测试。2025年12月4号，拨打110或者189202512043。123456块钱。"
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"在这个快速发展的时代，人工智能技术正在改变我们的生活方式。"
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"语音合成作为人工智能的重要应用之一，让机器能够用自然流畅的语音与人类进行交流。"
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)
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gen_config = sherpa_onnx.GenerationConfig()
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gen_config.sid = 0
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gen_config.speed = 1.0
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start = time.time()
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audio = tts.generate(text, gen_config)
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end = time.time()
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assert len(audio.samples) > 0, "No audio generated!"
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assert audio.sample_rate > 0, "Invalid sample rate!"
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filename = "test-matcha-zh-en-lexicon.wav"
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sf.write(filename, audio.samples, samplerate=audio.sample_rate)
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elapsed_seconds = end - start
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audio_duration = len(audio.samples) / audio.sample_rate
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rtf = elapsed_seconds / audio_duration
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print(f"Saved to {filename}")
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print(f"Elapsed seconds: {elapsed_seconds:.3f}")
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print(f"Audio duration in seconds: {audio_duration:.3f}")
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print(f"RTF: {elapsed_seconds:.3f}/{audio_duration:.3f} = {rtf:.3f}")
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