Initial commit

2026-02-06 20:31:14 +08:00
parent a0b51be095
commit c589bcb837
145 changed files with 28773 additions and 0 deletions
@@ -0,0 +1,100 @@
+import librosa
+import numpy as np
+import wave
+import soundfile as sf
+
+
+def librosa_pad_lr(x, fsize, fshift, pad_sides=1):
+    '''compute right padding (final frame) or both sides padding (first and final frames)
+    '''
+    assert pad_sides in (1, 2)
+    # return int(fsize // 2)
+    pad = (x.shape[0] // fshift + 1) * fshift - x.shape[0]
+    if pad_sides == 1:
+        return 0, pad
+    else:
+        return pad // 2, pad // 2 + pad % 2
+
+
+def amp_to_db(x):
+    return 20 * np.log10(np.maximum(1e-5, x))
+
+
+def db_to_amp(x):
+    return 10.0 ** (x * 0.05)
+
+
+def normalize(S, min_level_db):
+    return (S - min_level_db) / -min_level_db
+
+
+def denormalize(D, min_level_db):
+    return (D * -min_level_db) + min_level_db
+
+
+def librosa_wav2spec(wav_path,
+                     fft_size=1024,
+                     hop_size=256,
+                     win_length=1024,
+                     window="hann",
+                     num_mels=80,
+                     fmin=80,
+                     fmax=-1,
+                     eps=1e-6,
+                     sample_rate=22050,
+                     loud_norm=False,
+                     trim_long_sil=False):
+    import pyloudnorm as pyln
+    if isinstance(wav_path, str):
+        if trim_long_sil:
+            from .vad import trim_long_silences
+            wav, _, _ = trim_long_silences(wav_path, sample_rate)
+        else:
+            wav, _ = librosa.core.load(wav_path, sr=sample_rate)
+    else:
+        wav = wav_path
+    wav_orig = np.copy(wav)
+
+    if loud_norm:
+        meter = pyln.Meter(sample_rate)  # create BS.1770 meter
+        loudness = meter.integrated_loudness(wav)
+        wav = pyln.normalize.loudness(wav, loudness, -22.0)
+        if np.abs(wav).max() > 1:
+            wav = wav / np.abs(wav).max()
+
+    # get amplitude spectrogram
+    x_stft = librosa.stft(wav, n_fft=fft_size, hop_length=hop_size,
+                          win_length=win_length, window=window, pad_mode="constant")
+    linear_spc = np.abs(x_stft)  # (n_bins, T)
+
+    # get mel basis
+    fmin = 0 if fmin == -1 else fmin
+    fmax = sample_rate / 2 if fmax == -1 else fmax
+    mel_basis = librosa.filters.mel(sr=sample_rate, n_fft=fft_size, n_mels=num_mels, fmin=fmin, fmax=fmax)
+
+    # calculate mel spec
+    mel = mel_basis @ linear_spc
+    mel = np.log10(np.maximum(eps, mel))  # (n_mel_bins, T)
+    l_pad, r_pad = librosa_pad_lr(wav, fft_size, hop_size, 1)
+    wav = np.pad(wav, (l_pad, r_pad), mode='constant', constant_values=0.0)
+    wav = wav[:mel.shape[1] * hop_size]
+
+    # log linear spec
+    linear_spc = np.log10(np.maximum(eps, linear_spc))
+    return {'wav': wav, 'mel': mel.T, 'linear': linear_spc.T, 'mel_basis': mel_basis, 'wav_orig': wav_orig}
+
+def get_wav_num_frames(path, sr=None):
+    try:
+        with wave.open(path, 'rb') as f:
+            sr_ = f.getframerate()
+            if sr is None:
+                sr = sr_
+            return int(f.getnframes() / (sr_ / sr))
+    except wave.Error:
+        wav_file, sr_ = sf.read(path, dtype='float32')
+        if sr is None:
+                sr = sr_
+        return int(len(wav_file) / (sr_ / sr))
+    except:
+        wav_file, sr_ = librosa.core.load(path, sr=sr)
+        return len(wav_file)