def process(self, path, segment_length, sampling_rate):
        """
        Reads input and label audio files, and ensures the audio is segmented into
        the desired length, padding if necessary or extracting random segments if
        the audio is longer than the target segment length.

        Parameters:
        path (dict): Dictionary containing the paths to 'inputs' and 'labels' audio files.
        segment_length (int): Desired length of the audio segment in samples.
        sampling_rate (int): Target sample rate for the audio.

        Returns:
        tuple: A pair of numpy arrays representing the processed input and label audio,
               either padded to the segment length or trimmed.
        """
        # Read the input and label audio files using the target sampling rate.
        wave_inputs = audioread(path['inputs'], sampling_rate)
        wave_labels = audioread(path['labels'], sampling_rate)
        
        # Get the length of the label audio (assumed both inputs and labels have similar lengths).
        len_wav = wave_labels.shape[0]
        
        # If the input audio is shorter than the desired segment length, pad it with zeros.
        if wave_inputs.shape[0] < segment_length:
            # Create zero-padded arrays for inputs and labels.
            padded_inputs = np.zeros(segment_length, dtype=np.float32)
            padded_labels = np.zeros(segment_length, dtype=np.float32)
            
            # Copy the original audio into the padded arrays.
            padded_inputs[:wave_inputs.shape[0]] = wave_inputs
            padded_labels[:wave_labels.shape[0]] = wave_labels
        else:
            # Randomly select a start index for segmenting the audio if it's longer than the segment length.
            st_idx = random.randint(0, len_wav - segment_length)
            
            # Extract a segment of the desired length from the inputs and labels.
            padded_inputs = wave_inputs[st_idx:st_idx + segment_length]
            padded_labels = wave_labels[st_idx:st_idx + segment_length]
        
        # Return the processed (padded or segmented) input and label audio.
        return padded_inputs, padded_labels

        Reads input and label audio files, and ensures the audio is segmented into
        the desired length, padding if necessary or extracting random segments if
        the audio is longer than the target segment length.

        Parameters:
        path (dict): Dictionary containing the paths to 'inputs' and 'labels' audio files.
        segment_length (int): Desired length of the audio segment in samples.
        sampling_rate (int): Target sample rate for the audio.

        Returns:
        tuple: A pair of numpy arrays representing the processed input and label audio,
               either padded to the segment length or trimmed.
        
train/speech_super_resolution/dataloader/dataloader.py