wav_to_spectro.py

import numpy as np
import resampy
from scipy.io import wavfile
import pdb
import mel_features
import params

def shorter_waveform_to_examples(data):
    """
    Compute the spectrogram for each short audios
    Input: short audio data
    Output: list of spectrograms in this short audio, eahch with params.EXAMPLE_WINDOW_SECONDS, hopped by params.EXAMPLE_HOP_SECONDS
    """
    # Compute log mel spectrogram features for each short audios
    log_mel = mel_features.log_mel_spectrogram(
        data,
        audio_sample_rate=params.SAMPLE_RATE,
        log_offset=params.LOG_OFFSET,
        window_length_secs=params.STFT_WINDOW_LENGTH_SECONDS,
        hop_length_secs=params.STFT_HOP_LENGTH_SECONDS,
        num_mel_bins=params.NUM_MEL_BINS, # here forced the num_mel_bins
        lower_edge_hertz=params.MEL_MIN_HZ,
        upper_edge_hertz=params.MEL_MAX_HZ)

    #(data.shape[0]/params.SAMPLE_RATE*1000-25)/10+1 FRAMES x num_mel_bins

    # Frame features into examples
    # Each example is [100x513]->[100x64bins] (non-overlapping)
    features_sample_rate = 1.0 / params.STFT_HOP_LENGTH_SECONDS #frames every second
    example_window_length = int(round(params.EXAMPLE_WINDOW_SECONDS * features_sample_rate))
    example_hop_length = int(round(params.EXAMPLE_HOP_SECONDS * features_sample_rate))
    log_mel_examples = mel_features.frame(
        log_mel,
        window_length=example_window_length,
        hop_length=example_hop_length)
    return log_mel_examples

def segment_long_audio(wav_file):
    """ segment the long audio into short audios, with duration of params.SHORT_AUDIO_WINDOW_LENGTH_MIN,
    overlapped by params.SHORT_AUDIO_HOP_LENGTH_MIN
    Input: original long audio wav file
    Output: list of its short audios
    """
    sample_rate, wav_data = wavfile.read(wav_file) # single audio file
    assert wav_data.dtype == np.int16, 'Bad sample type: %r' % wav_data.dtype
    data = wav_data / 32768.0  # Convert to [-1.0, +1.0]
    # Convert to mono.
    if len(data.shape) > 1:
        data = np.mean(data, axis=1)
    if len(data) == 0:
        return 0

    # Resample to the 16000
    if sample_rate != params.SAMPLE_RATE:
        data = resampy.resample(data, sample_rate, vggish_params.SAMPLE_RATE)

    # frame the long audio into shorter ones
    data_example_window_length = params.SHORT_AUDIO_WINDOW_LENGTH_MIN * 60 * params.SAMPLE_RATE
    data_example_hop_length = params.SHORT_AUDIO_HOP_LENGTH_MIN * 60 * params.SAMPLE_RATE
    data_examples = mel_features.frame(
        data,
        window_length=data_example_window_length,
        hop_length=data_example_hop_length)
    return data_examples

def wavfile_to_examples(wav_file):
    sample_rate, wav_data = wavfile.read(wav_file)
    assert wav_data.dtype == np.int16, 'Bad sample type: %r' % wav_data.dtype
    data = wav_data / 32768.0  # Convert to [-1.0, +1.0]
    # Convert to mono.
    if len(data.shape) > 1:
        data = np.mean(data, axis=1)
    if len(data) == 0:
        return 0
    if sample_rate != params.SAMPLE_RATE:
        data = resampy.resample(data, sample_rate, params.SAMPLE_RATE)

    # Compute log mel spectrogram features for each short audios (log FBANK)
    log_mel = mel_features.log_mel_spectrogram(
        data,
        audio_sample_rate=params.SAMPLE_RATE,
        log_offset=params.LOG_OFFSET,
        window_length_secs=params.STFT_WINDOW_LENGTH_SECONDS,
        hop_length_secs=params.STFT_HOP_LENGTH_SECONDS,
        num_mel_bins=params.NUM_MEL_BINS, # here forced the num_mel_bins
        lower_edge_hertz=params.MEL_MIN_HZ,
        upper_edge_hertz=params.MEL_MAX_HZ)

    features_sample_rate = 1.0 / params.STFT_HOP_LENGTH_SECONDS
    example_window_length = int(round(params.EXAMPLE_WINDOW_SECONDS * features_sample_rate))
    example_hop_length = int(round(params.EXAMPLE_HOP_SECONDS * features_sample_rate))

    # added: zero pad the frame to expected frame number for each example log-mel FBANK
    if log_mel.shape[0] % params.NUM_FRAMES:
        pad_data = np.zeros((int(np.ceil(1.0*log_mel.shape[0]/params.NUM_FRAMES)*params.NUM_FRAMES),log_mel.shape[1]))
        pad_data[:log_mel.shape[0],:log_mel.shape[1]] = log_mel
        log_mel = pad_data

    log_mel_examples = mel_features.frame(
        log_mel,
        window_length=example_window_length,
        hop_length=example_hop_length)
    return log_mel_examples