competition update

language_model/tools/compute_fbank_feats.py

@@ -0,0 +1,128 @@
+# Copyright (c) 2020 Mobvoi Inc. (authors: Binbin Zhang, Chao Yang)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import argparse
+import logging
+
+import torchaudio
+import torchaudio.compliance.kaldi as kaldi
+
+import wenet.dataset.kaldi_io as kaldi_io
+
+# The "sox" backends are deprecated and will be removed in 0.9.0 release.
+# So here we use sox_io backend
+torchaudio.set_audio_backend("sox_io")
+
+
+def parse_opts():
+    parser = argparse.ArgumentParser(description='training your network')
+    parser.add_argument('--num_mel_bins',
+                        default=80,
+                        type=int,
+                        help='Number of triangular mel-frequency bins')
+    parser.add_argument('--frame_length',
+                        type=int,
+                        default=25,
+                        help='Frame length in milliseconds')
+    parser.add_argument('--frame_shift',
+                        type=int,
+                        default=10,
+                        help='Frame shift in milliseconds')
+    parser.add_argument('--dither',
+                        type=int,
+                        default=0.0,
+                        help='Dithering constant (0.0 means no dither)')
+    parser.add_argument('--segments', default=None, help='segments file')
+    parser.add_argument('wav_scp', help='wav scp file')
+    parser.add_argument('out_ark', help='output ark file')
+    parser.add_argument('out_scp', help='output scp file')
+    args = parser.parse_args()
+    return args
+
+
+# wav format: <key> <wav_path>
+def load_wav_scp(wav_scp_file):
+    wav_list = []
+    with open(wav_scp_file, 'r', encoding='utf8') as fin:
+        for line in fin:
+            arr = line.strip().split()
+            assert len(arr) == 2
+            wav_list.append((arr[0], arr[1]))
+    return wav_list
+
+
+# wav format: <key> <wav_path>
+def load_wav_scp_dict(wav_scp_file):
+    wav_dict = {}
+    with open(wav_scp_file, 'r', encoding='utf8') as fin:
+        for line in fin:
+            arr = line.strip().split()
+            assert len(arr) == 2
+            wav_dict[arr[0]] = arr[1]
+    return wav_dict
+
+
+# Segments format: <key> <wav_key> <start> <end>
+def load_wav_segments(wav_scp_file, segments_file):
+    wav_dict = load_wav_scp_dict(wav_scp_file)
+    audio_list = []
+    with open(segments_file, 'r', encoding='utf8') as fin:
+        for line in fin:
+            arr = line.strip().split()
+            assert len(arr) == 4
+            key = arr[0]
+            wav_file = wav_dict[arr[1]]
+            start = float(arr[2])
+            end = float(arr[3])
+            audio_list.append((key, wav_file, start, end))
+    return audio_list
+
+
+if __name__ == '__main__':
+    args = parse_opts()
+    logging.basicConfig(level=logging.DEBUG,
+                        format='%(asctime)s %(levelname)s %(message)s')
+    if args.segments is None:
+        audio_list = load_wav_scp(args.wav_scp)
+    else:
+        audio_list = load_wav_segments(args.wav_scp, args.segments)
+
+    count = 0
+    with open(args.out_ark, 'wb') as ark_fout, \
+         open(args.out_scp, 'w', encoding='utf8') as scp_fout:
+        for item in audio_list:
+            if len(item) == 2:
+                key, wav_path = item
+                waveform, sample_rate = torchaudio.load_wav(wav_path)
+            else:
+                assert len(item) == 4
+                key, wav_path, start, end = item
+                sample_rate = torchaudio.info(wav_path).sample_rate
+                frame_offset = int(start * sample_rate)
+                num_frames = int((end - start) * sample_rate)
+                waveform, sample_rate = torchaudio.load_wav(
+                    wav_path, frame_offset, num_frames)
+
+            mat = kaldi.fbank(waveform,
+                              num_mel_bins=args.num_mel_bins,
+                              frame_length=args.frame_length,
+                              frame_shift=args.frame_shift,
+                              dither=args.dither,
+                              energy_floor=0.0,
+                              sample_frequency=sample_rate)
+            mat = mat.detach().numpy()
+            kaldi_io.write_ark_scp(key, mat, ark_fout, scp_fout)
+            count += 1
+            if count % 10000 == 0:
+                logging.info('Progress {}/{}'.format(count, len(audio_list)))