def audioread(path, sampling_rate, use_norm):
    """
    Reads an audio file from the specified path, normalizes the audio,
    resamples it to the desired sampling rate (if necessary), and ensures it is single-channel.

    Parameters:
    path (str): The file path of the audio file to be read.
    sampling_rate (int): The target sampling rate for the audio.
    use_norm (bool): The flag for specifying whether using input audio normalization

    Returns:
    numpy.ndarray: The processed audio data, normalized, resampled (if necessary),
                   and converted to mono (if the input audio has multiple channels).
    """
    
    # Read audio data and its sample rate from the file.
    audio_info = {}
    ext = get_file_extension(path).replace('.', '')
    audio_info['ext']=ext
    data = read_audio(path)
    if data is None: return None, None, None
   
    audio_info['sample_rate'] = data.frame_rate
    audio_info['channels'] = data.channels
    audio_info['sample_width'] = data.sample_width

    data_array = np.array(data.get_array_of_samples())
    if max(data_array) > MAX_WAV_VALUE_16B:
        audio_np = data_array / MAX_WAV_VALUE_32B
    else:
        audio_np = data_array / MAX_WAV_VALUE_16B

    audios = []
    # Check if the audio is stereo
    if audio_info['channels'] == 2:
        audios.append(audio_np[::2])  # Even indices (left channel)
        audios.append(audio_np[1::2])  # Odd indices (right channel)
    else:
        audios.append(audio_np)
    
    # Normalize the audio data.
    audios_normed = []
    scalars = []
    for audio in audios:
        if use_norm:
            audio_normed, scalar = audio_norm(audio)
            audios_normed.append(audio_normed)
            scalars.append(scalar)
        else:
            audios_normed.append(audio)
            scalars.append(1)
    # Resample the audio if the sample rate is different from the target sampling rate.
    if audio_info['sample_rate'] != sampling_rate:
        index = 0
        for audio_normed in audios_normed:
            audios_normed[index] = librosa.resample(audio_normed, orig_sr=audio_info['sample_rate'], target_sr=sampling_rate)
            index = index + 1
    
    # Return the processed audio data.
    return audios_normed, scalars, audio_info

    Reads an audio file from the specified path, normalizes the audio,
    resamples it to the desired sampling rate (if necessary), and ensures it is single-channel.

    Parameters:
    path (str): The file path of the audio file to be read.
    sampling_rate (int): The target sampling rate for the audio.
    use_norm (bool): The flag for specifying whether using input audio normalization

    Returns:
    numpy.ndarray: The processed audio data, normalized, resampled (if necessary),
                   and converted to mono (if the input audio has multiple channels).
    
train/speech_super_resolution/dataloader/dataloader.py