ASLP-lab/WSYue-TTS

👉🏻 WenetSpeech-Yue 👈🏻

WenetSpeech-Yue: Demos; Paper; Github; HuggingFace

📢 News and Updates

• 2025.11.15 🚀 Released Llasa-1B-Yue-Updated！ You can access the complete inference pipeline and scripts on WenetSpeech-Yue

Highlight🔥

WenetSpeech-Yue TTS Models have been released!
This repository contains two versions of the TTS models:

1. ASLP-lab/Cosyvoice2-Yue: The base model for Cantonese TTS.
2. ASLP-lab/Cosyvoice2-Yue-ZoengJyutGaai: A fine-tuned, higher-quality version for more natural speech generation.

Install

Clone and install

• Clone the repo

git clone https://github.com/ASLP-lab/WenetSpeech-Yue.git
cd WenetSpeech-Yue/CosyVoice2-Yue

• Create Conda env:

conda create -n cosyvoice python=3.10
conda activate cosyvoice
# pynini is required by WeTextProcessing, use conda to install it as it can be executed on all platform.
conda install -y -c conda-forge pynini==2.1.5
pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/ --trusted-host=mirrors.aliyun.com

Model download

from huggingface_hub import snapshot_download
snapshot_download('ASLP-lab/Cosyvoice2-Yue', local_dir='pretrained_models/Cosyvoice2-Yue')
snapshot_download('ASLP-lab/Cosyvoice2-Yue-ZoengJyutGaai', local_dir='pretrained_models/Cosyvoice2-Yue-ZoengJyutGaai')

Usage

import sys
sys.path.append('third_party/Matcha-TTS')
from cosyvoice.cli.cosyvoice import CosyVoice, CosyVoice2
from cosyvoice.utils.file_utils import load_wav
import torchaudio
import opencc

# s2t
converter = opencc.OpenCC('s2t.json')

cosyvoice_base = CosyVoice2(
    'pretrained_models/Cosyvoice2-Yue',
    load_jit=False, load_trt=False, load_vllm=False, fp16=False
)

cosyvoice_zjg = CosyVoice2(
    'pretrained_models/Cosyvoice2-Yue-ZoengJyutGaai',
    load_jit=False, load_trt=False, load_vllm=False, fp16=False
)

prompt_speech_16k = load_wav('asset/sg_017_090.wav', 16000)

text = '收到朋友从远方寄嚟嘅生日礼物，嗰份意外嘅惊喜同埋深深嘅祝福令我心入面充满咗甜蜜嘅快乐，笑容好似花咁绽放。'
text = converter.convert(text)

for i, j in enumerate(cosyvoice_base.inference_instruct2(text, '用粤语说这句话', prompt_speech_16k, stream=False)):
    torchaudio.save('base_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)

for i, j in enumerate(cosyvoice_zjg.inference_instruct2(text, '用粤语说这句话', prompt_speech_16k, stream=False)):
    torchaudio.save('zjg_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)

Contact

If you are interested in leaving a message to our research team, feel free to email lhli@mail.nwpu.edu.cn or gzhao@mail.nwpu.edu.cn.