add cosyvoice code

tools/extract_embedding.py

@@ -0,0 +1,67 @@
+#!/usr/bin/env python3
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# 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 torch
+import torchaudio
+from tqdm import tqdm
+import onnxruntime
+import torchaudio.compliance.kaldi as kaldi
+
+
+def main(args):
+    utt2wav, utt2spk = {}, {}
+    with open('{}/wav.scp'.format(args.dir)) as f:
+        for l in f:
+            l = l.replace('\n', '').split()
+            utt2wav[l[0]] = l[1]
+    with open('{}/utt2spk'.format(args.dir)) as f:
+        for l in f:
+            l = l.replace('\n', '').split()
+            utt2spk[l[0]] = l[1]
+
+    option = onnxruntime.SessionOptions()
+    option.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL
+    option.intra_op_num_threads = 1
+    providers = ["CPUExecutionProvider"]
+    ort_session = onnxruntime.InferenceSession(args.onnx_path, sess_options=option, providers=providers)
+
+    utt2embedding, spk2embedding = {}, {}
+    for utt in tqdm(utt2wav.keys()):
+        audio, sample_rate = torchaudio.load(utt2wav[utt])
+        if sample_rate != 16000:
+            audio = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=16000)(audio)
+        feat = kaldi.fbank(audio,
+                           num_mel_bins=80,
+                           dither=0,
+                           sample_frequency=16000)
+        feat = feat - feat.mean(dim=0, keepdim=True)
+        embedding = ort_session.run(None, {ort_session.get_inputs()[0].name: feat.unsqueeze(dim=0).cpu().numpy()})[0].flatten().tolist()
+        utt2embedding[utt] = embedding
+        spk = utt2spk[utt]
+        if spk not in spk2embedding:
+            spk2embedding[spk] = []
+        spk2embedding[spk].append(embedding)
+
+    torch.save(utt2embedding, '{}/utt2embedding.pt'.format(args.dir))
+    torch.save(spk2embedding, '{}/spk2embedding.pt'.format(args.dir))
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--dir',
+                        type=str)
+    parser.add_argument('--onnx_path',
+                        type=str)
+    args = parser.parse_args()
+    main(args)