def METHOD_NAME(self, inputs: List[str],
               **preprocess_params) -> Dict[str, Any]:
    if len(inputs) != 2:
        raise ValueError(
            'modelscope error: Two input audio files are required.')
    output = {}
    for i in range(len(inputs)):
        if isinstance(inputs[i], str):
            file_bytes = File.read(inputs[i])
            data, fs = sf.read(io.BytesIO(file_bytes), dtype='float32')
            if len(data.shape) == 2:
                data = data[:, 0]
            if fs != self.model_config['sample_rate']:
                raise ValueError(
                    'modelscope error: Only support %d sample rate files'
                    % self.model_cfg['sample_rate'])
            output['data%d' %
                   (i + 1)] = torch.from_numpy(data).unsqueeze(0)
        else:
            raise ValueError(
                'modelscope error: The input type is temporarily restricted to audio file address'
                % i)
    return output