Qwen3-TTS-TBLive-CustomVoice

Qwen3-TTS-TBLive-CustomVoice

A CustomVoice checkpoint fine-tuned from TaoLiveAIGC/Qwen3-TTS-TBLive-Base. It ships six built-in open-source speakers spanning three live-streaming styles — professional presentation (专业讲解), warm recommendation (贴心推荐), and energetic promotion (激情促销) — each in a female and a male voice, plus inline instruction-control tokens for pause and speaking-rate control.

Built-in speakers

Pass the speaker ID to generate_custom_voice(text, speaker=...):

Instruction control tokens

Insert the following tokens directly into the input text; they are interpreted inline at the position where they appear.

Silence / pause tokens — each token synthesizes a pause within a fixed duration band:

Speed tokens — like silence tokens, they can be inserted anywhere in the text and adjust the speaking rate of the speech that follows:

Quickstart

pip install -U qwen-tts

import torch
from qwen_tts import Qwen3TTSModel

model = Qwen3TTSModel.from_pretrained(
    "TaoLiveAIGC/Qwen3-TTS-TBLive-CustomVoice",
    device_map="cuda:0",
    dtype=torch.bfloat16,
)

wavs, sr = model.generate_custom_voice(
    text="[speed_e2] 家人们，最后一波福利来了！<sil_L3> 库存不多，喜欢的抓紧下单！",
    speaker="4",  # 激情促销女
)

For speaker registration (baking new speakers into a fine-tuned checkpoint), training pipelines, and inference post-selection, see the companion training repository. For upstream features (vLLM serving, DashScope API, deployment), refer to the upstream Qwen3-TTS repository.

Checkpoint contents

├── model.safetensors            # main checkpoint (~3.6 GB, six speakers baked in)
├── config.json / configuration.json / generation_config.json
├── preprocessor_config.json
├── tokenizer_config.json / vocab.json / merges.txt
├── tokenizer.json / added_tokens.json / special_tokens_map.json
└── speech_tokenizer/            # 12 Hz speech tokenizer (~651 MB, same as upstream)

License

Released under the Apache License 2.0, consistent with upstream Qwen3-TTS.

Acknowledgements

Our sincere thanks to the Qwen team for open-sourcing Qwen3-TTS — the base model, tokenizer, and reference training / inference code that make this work possible.