| --- |
| license: apache-2.0 |
| pipeline_tag: text-to-speech |
| language: |
| - zh |
| - en |
| - de |
| - fr |
| - ja |
| - ko |
| tags: |
| - m5-tts |
| - custom-voice |
| - multilingual |
| - pytorch |
| --- |
| |
| # M5-TTS-50M-CustomVoice |
|
|
| English | [简体中文](README_zh.md) |
|
|
| [GitHub](https://github.com/ASLP-lab/M5-TTS) · [Demo](https://aslp-lab.github.io/M5-TTS-Demo-Page/) · [Space](https://huggingface.co/spaces/ASLP-lab/M5-TTS-Space) · [Models](https://huggingface.co/collections/ASLP-lab/m5-tts) |
|
|
| **M5-TTS** is a compact multilingual and multi-dialect text-to-speech system from ASLP@NPU and LycheeAI Lab. It combines a 30M temporal backbone with a 20M local multi-token prediction decoder, using 16 audio codebooks at 12.5 frames/s for **24 kHz** speech generation. The speech codec is separate. |
|
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| **CustomVoice** is the dedicated checkpoint for preset-speaker synthesis: provide text and a trained speaker ID, with **no reference audio or reference transcript required**. The example below uses speaker ID `1`. Available IDs and voice capabilities depend on the checkpoint. |
|
|
| ## Quickstart |
|
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| Use Python 3.10 on Linux with a BF16-capable NVIDIA GPU and a compatible CUDA driver. Install from the code repository: |
|
|
| ```bash |
| git clone https://github.com/ASLP-lab/M5-TTS.git |
| cd M5-TTS |
| conda create -n m5tts python=3.10 -y |
| conda activate m5tts |
| pip install -r requirements.txt |
| pip install --no-build-isolation flash-attn==2.7.3 |
| ``` |
|
|
| Run from the repository root: |
|
|
| ```bash |
| python infer_speaker.py \ |
| --model ASLP-lab/M5-TTS-50M-CustomVoice \ |
| --text "你好，今天的天气很好，适合出去散散步。" \ |
| --speaker-id 1 \ |
| --output outputs/speaker.wav |
| ``` |
|
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| The M5 checkpoint, text tokenizer and [audio tokenizer](https://huggingface.co/ASLP-lab/M5-TTS-Audio-Tokenizer) are downloaded automatically. Use `--lang Chinese`, `English`, `German`, `French`, `Japanese` or `Korean` to set the target language. |
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| This checkpoint is different from [VoiceClone](https://huggingface.co/ASLP-lab/M5-TTS-50M-VoiceClone). Setting a speaker ID does not switch a loaded model's weights. See the [project README](https://github.com/ASLP-lab/M5-TTS#quickstart) for Python API usage and evaluation results. |
|
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| ## License |
|
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| Apache-2.0. The Qwen-derived audio codec retains its upstream attribution; see the [third-party notice](https://github.com/ASLP-lab/M5-TTS/blob/main/m5/codec_qwen12hz/NOTICE). |
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|
