add a script to compute sampling weight

egs/audioset/AT/local/compute_weight.py

@@ -0,0 +1,73 @@
+#!/usr/bin/env python3
+# Copyright    2023  Xiaomi Corp.        (authors: Xiaoyu Yang)
+#
+# See ../../../../LICENSE for clarification regarding multiple authors
+#
+# 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.
+
+"""
+This file generates the manifest and computes the fbank features for AudioSet
+dataset. The generated manifests and features are stored in data/fbank.
+"""
+
+import argparse
+
+import lhotse
+from lhotse import load_manifest
+
+def get_parser():
+    parser = argparse.ArgumentParser(
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter
+    )
+
+    parser.add_argument(
+        "--input-manifest",
+        type=str,
+        default="data/fbank/cuts_audioset_full.jsonl.gz"
+    )
+
+    parser.add_argument(
+        "--output",
+        type=str,
+        required=True,
+
+    )
+    return parser
+
+def main():
+    # Reference: https://github.com/YuanGongND/ast/blob/master/egs/audioset/gen_weight_file.py
+    parser = get_parser()
+    args = parser.parse_args()
+
+    cuts = load_manifest(args.input_manifest)
+
+    print(f"A total of {len(cuts)} cuts.")
+
+    label_count = [0] * 527 # a total of 527 classes
+    for c in cuts:
+        audio_event = c.supervisions[0].audio_event
+        labels = list(map(int, audio_event.split(";")))
+        for label in labels:
+            label_count[label] += 1
+
+    with open(args.output, "w") as f:
+        for c in cuts:
+            audio_event = c.supervisions[0].audio_event
+            labels = list(map(int, audio_event.split(";")))
+            weight = 0
+            for label in labels:
+                weight += 1000 / (label_count[label] + 0.01)
+            f.write(f"{c.id} {weight}\n")
+            
+if __name__ == "__main__":
+    main()