Whisper Large V3 Narrow Accent

🚀 Whisper-Large v3 用于窄口音分类

本模型用于实现窄口音分类，可有效解决对不同英语口音进行精准分类的问题，为语音识别和分析领域提供了有力支持。

🚀 快速开始

下载仓库

git clone git@github.com:tiantiaf0627/vox-profile-release.git

安装包

conda create -n vox_profile python=3.8
cd vox-profile-release
pip install -e .

加载模型

# Load libraries
import torch
import torch.nn.functional as F
from src.model.accent.whisper_accent import WhisperWrapper

# Find device
device = torch.device("cuda") if torch.cuda.is_available() else "cpu"

# Load model from Huggingface
model = WhisperWrapper.from_pretrained("tiantiaf/whisper-large-v3-narrow-accent").to(device)
model.eval()

预测

# Label List
english_accent_list = [
    'East Asia', 'English', 'Germanic', 'Irish', 
    'North America', 'Northern Irish', 'Oceania', 
    'Other', 'Romance', 'Scottish', 'Semitic', 'Slavic', 
    'South African', 'Southeast Asia', 'South Asia', 'Welsh'
]
    
# Load data, here just zeros as the example
# Our training data filters output audio shorter than 3 seconds (unreliable predictions) and longer than 15 seconds (computation limitation)
# So you need to prepare your audio to a maximum of 15 seconds, 16kHz and mono channel
max_audio_length = 15 * 16000
data = torch.zeros([1, 16000]).float().to(device)[:, :max_audio_length]
logits, embeddings = model(data, return_feature=True)
    
# Probability and output
accent_prob = F.softmax(logits, dim=1)
print(english_accent_list[torch.argmax(accent_prob).detach().cpu().item()])

✨ 主要特性

本模型包含了在《Vox-Profile: A Speech Foundation Model Benchmark for Characterizing Diverse Speaker and Speech Traits》(https://arxiv.org/pdf/2505.14648) 中描述的窄口音分类的实现。包含的英语口音有：

[
  'East Asia', 'English', 'Germanic', 'Irish', 
  'North America', 'Northern Irish', 'Oceania', 
  'Other', 'Romance', 'Scottish', 'Semitic', 'Slavic', 
  'South African', 'Southeast Asia', 'South Asia', 'Welsh'
]

模型的一些观察结果（随着观察增加会持续补充）：

1. 文本转语音（TTS）样本更倾向于被识别为日耳曼口音。

• 相关库：https://github.com/tiantiaf0627/vox-profile-release

📚 详细文档

引用信息

如果您使用了我们的模型或发现它在您的工作中很有用，请引用我们的论文：

@article{feng2025vox,
  title={Vox-Profile: A Speech Foundation Model Benchmark for Characterizing Diverse Speaker and Speech Traits},
  author={Feng, Tiantian and Lee, Jihwan and Xu, Anfeng and Lee, Yoonjeong and Lertpetchpun, Thanathai and Shi, Xuan and Wang, Helin and Thebaud, Thomas and Moro-Velazquez, Laureano and Byrd, Dani and others},
  journal={arXiv preprint arXiv:2505.14648},
  year={2025}
}

📄 许可证

本模型采用 BSD 3 条款许可证（bsd-3-clause）。

📦 模型信息