utils.py

# -*- coding: utf-8 -*-
#/usr/bin/python2

from __future__ import print_function

import librosa
import numpy as np
from scipy import signal


def spectrogram2wav(mag, n_fft, win_length, hop_length, num_iters, phase_angle=None, length=None):
    assert(num_iters > 0)
    if phase_angle is None:
        phase_angle = np.pi * np.random.rand(*mag.shape)
    spec = mag * np.exp(1.j * phase_angle)
    for i in range(num_iters):
        wav = librosa.istft(spec, win_length=win_length, hop_length=hop_length, length=length)
        if i != num_iters - 1:
            spec = librosa.stft(wav, n_fft=n_fft, win_length=win_length, hop_length=hop_length)
            _, phase = librosa.magphase(spec)
            phase_angle = np.angle(phase)
            spec = mag * np.exp(1.j * phase_angle)
    return wav


def preemphasis(x, coeff=0.97):
  return signal.lfilter([1, -coeff], [1], x)


def inv_preemphasis(x, coeff=0.97):
  return signal.lfilter([1], [1, -coeff], x)


def wav_random_crop(wav, sr, duration):
    assert (wav.ndim <= 2)

    target_len = sr * duration
    wav_len = wav.shape[-1]
    start = np.random.choice(range(np.maximum(1, wav_len - target_len)), 1)[0]
    end = start + target_len
    if wav.ndim == 1:
        wav = wav[start:end]
    else:
        wav = wav[:, start:end]
    return wav