add files

funasr_local/models/frontend/eend_ola_feature.py

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+# Copyright 2019 Hitachi, Ltd. (author: Yusuke Fujita)
+# Licensed under the MIT license.
+#
+# This module is for computing audio features
+
+import librosa
+import numpy as np
+
+
+def transform(Y, dtype=np.float32):
+    Y = np.abs(Y)
+    n_fft = 2 * (Y.shape[1] - 1)
+    sr = 8000
+    n_mels = 23
+    mel_basis = librosa.filters.mel(sr, n_fft, n_mels)
+    Y = np.dot(Y ** 2, mel_basis.T)
+    Y = np.log10(np.maximum(Y, 1e-10))
+    mean = np.mean(Y, axis=0)
+    Y = Y - mean
+    return Y.astype(dtype)
+
+
+def subsample(Y, T, subsampling=1):
+    Y_ss = Y[::subsampling]
+    T_ss = T[::subsampling]
+    return Y_ss, T_ss
+
+
+def splice(Y, context_size=0):
+    Y_pad = np.pad(
+        Y,
+        [(context_size, context_size), (0, 0)],
+        'constant')
+    Y_spliced = np.lib.stride_tricks.as_strided(
+        np.ascontiguousarray(Y_pad),
+        (Y.shape[0], Y.shape[1] * (2 * context_size + 1)),
+        (Y.itemsize * Y.shape[1], Y.itemsize), writeable=False)
+    return Y_spliced
+
+
+def stft(
+        data,
+        frame_size=1024,
+        frame_shift=256):
+    fft_size = 1 << (frame_size - 1).bit_length()
+    if len(data) % frame_shift == 0:
+        return librosa.stft(data, n_fft=fft_size, win_length=frame_size,
+                            hop_length=frame_shift).T[:-1]
+    else:
+        return librosa.stft(data, n_fft=fft_size, win_length=frame_size,
+                            hop_length=frame_shift).T