def preprocess(
        self, payload: FileData | None
    ) -> str | tuple[int, np.ndarray] | None:
        """
        Parameters:
            payload: audio data as a FileData object, or None.
        Returns:
            passes audio as one of these formats (depending on `type`): a `str` filepath, or `tuple` of (sample rate in Hz, audio data as numpy array). If the latter, the audio data is a 16-bit `int` array whose values range from -32768 to 32767 and shape of the audio data array is (samples,) for mono audio or (samples, channels) for multi-channel audio.
        """
        if payload is None:
            return payload

        if not payload.path:
            raise ValueError("payload path missing")

        needs_conversion = False
        original_suffix = Path(payload.path).suffix.lower()
        if self.format is not None and original_suffix != f".{self.format}":
            needs_conversion = True

        if self.min_length is not None or self.max_length is not None:
            sample_rate, data = processing_utils.audio_from_file(payload.path)
            duration = len(data) / sample_rate
            if self.min_length is not None and duration < self.min_length:
                raise Error(
                    f"Audio is too short, and must be at least {self.min_length} seconds"
                )
            if self.max_length is not None and duration > self.max_length:
                raise Error(
                    f"Audio is too long, and must be at most {self.max_length} seconds"
                )

        if self.type == "numpy":
            return processing_utils.audio_from_file(payload.path)
        elif self.type == "filepath":
            if not needs_conversion:
                return payload.path
            sample_rate, data = processing_utils.audio_from_file(payload.path)
            output_file = str(Path(payload.path).with_suffix(f".{self.format}"))
            assert self.format is not None  # noqa: S101
            processing_utils.audio_to_file(
                sample_rate, data, output_file, format=self.format
            )
            return output_file
        else:
            raise ValueError(
                "Unknown type: "
                + str(self.type)
                + ". Please choose from: 'numpy', 'filepath'."
            )

        Parameters:
            payload: audio data as a FileData object, or None.
        Returns:
            passes audio as one of these formats (depending on `type`): a `str` filepath, or `tuple` of (sample rate in Hz, audio data as numpy array). If the latter, the audio data is a 16-bit `int` array whose values range from -32768 to 32767 and shape of the audio data array is (samples,) for mono audio or (samples, channels) for multi-channel audio.
        
gradio/components/audio.py