mamba语音识别代码

### Mamba 语音识别示例代码

Mamba 是一种先进的多模态大语言模型，在处理长序列任务如音频波形和DNA序列方面表现出色[^2]。下面是一个基于 Python 的简化版 Mamba 用于语音识别的示例代码：

import torch
from mamba.models import MambaForSpeechRecognition, WavFeatureExtractor

def load_model():
    model_name_or_path = "path_to_mamba_pretrained_model"
    feature_extractor = WavFeatureExtractor.from_pretrained(model_name_or_path)
    model = MambaForSpeechRecognition.from_pretrained(model_name_or_path)
    
    return model, feature_extractor

def transcribe_audio(audio_file):
    model, feature_extractor = load_model()
    
    # 加载并预处理音频文件
    speech_array, sampling_rate = torchaudio.load(audio_file)
    input_values = feature_extractor(
        speech_array.squeeze().numpy(), 
        sampling_rate=sampling_rate,
        return_tensors="pt",
        padding=True
    ).input_values
    
    with torch.no_grad():
        logits = model(input_values).logits
        
    predicted_ids = torch.argmax(logits, dim=-1)
    transcription = feature_extractor.decode(predicted_ids[0].tolist())
    
    return transcription

if __name__ == "__main__":
    audio_file = "example.wav"
    result = transcribe_audio(audio_file)
    print(f"Transcription: {result}")

此代码展示了如何加载预先训练好的 Mamba 模型以及如何使用该模型来转录给定的音频文件。需要注意的是，实际应用中可能还需要考虑更多细节，比如错误处理、优化推理速度等。