请帮我用bert和pytorch写一个用于提取音频特征的神经网络代码

我可以回答这个问题。以下是一个使用BERT和PyTorch编写的神经网络代码，用于提取音频特征：

import torch
from transformers import BertModel, BertTokenizer

class AudioFeatureExtractor(torch.nn.Module):
    def __init__(self, bert_model_name):
        super(AudioFeatureExtractor, self).__init__()
        self.bert = BertModel.from_pretrained(bert_model_name)
        self.tokenizer = BertTokenizer.from_pretrained(bert_model_name)

    def forward(self, audio_file):
        # Load audio file and convert to spectrogram
        spectrogram = convert_to_spectrogram(audio_file)

        # Convert spectrogram to text using the tokenizer
        text = convert_to_text(spectrogram, self.tokenizer)

        # Feed text through BERT model to get embeddings
        embeddings = self.bert(text)[0]

        # Average embeddings to get final audio feature vector
        feature_vector = torch.mean(embeddings, dim=0)

        return feature_vector

请注意，这只是一个示例代码，您需要根据您的具体需求进行修改和调整。