1 files changed, 65 insertions, 0 deletions
diff --git a/scripts/py/rnnoise_dump_extractor.py b/scripts/py/rnnoise_dump_extractor.py
new file mode 100644
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+++ b/scripts/py/rnnoise_dump_extractor.py
@@ -0,0 +1,65 @@
+#  Copyright (c) 2021 Arm Limited. All rights reserved.
+#  SPDX-License-Identifier: Apache-2.0
+#
+#  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 script can be used with the noise reduction use case to save
+the dumped noise reduced audio to a wav file.
+
+Example use:
+python rnnoise_dump_extractor.py --dump_file output.bin --output_dir ./denoised_wavs/
+"""
+import soundfile as sf
+import numpy as np
+
+import argparse
+from os import path
+
+import struct
+
+def extract(fp, output_dir, export_npy):
+    while True:
+        filename_length = struct.unpack("i", fp.read(4))[0]
+
+        if filename_length == -1:
+            return
+
+        filename = struct.unpack("{}s".format(filename_length), fp.read(filename_length))[0].decode('ascii')
+        audio_clip_length = struct.unpack("I", fp.read(4))[0]
+        output_file_name = path.join(output_dir, "denoised_{}".format(filename))
+        audio_clip = fp.read(audio_clip_length)
+        
+        with sf.SoundFile(output_file_name, 'w', channels=1, samplerate=48000, subtype="PCM_16", endian="LITTLE") as wav_file:
+            wav_file.buffer_write(audio_clip, dtype='int16')
+            print("{} written to disk".format(output_file_name))
+
+        if export_npy:
+            output_file_name += ".npy"
+            pack_format = "{}h".format(int(audio_clip_length/2))
+            npdata = np.array(struct.unpack(pack_format,audio_clip)).astype(np.int16)
+            np.save(output_file_name, npdata)
+            print("{} written to disk".format(output_file_name))
+
+def main(args):
+    extract(args.dump_file, args.output_dir, args.export_npy)
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--dump_file", type=argparse.FileType('rb'), help="Dump file with audio files to extract.", required=True)
+parser.add_argument("--output_dir", help="Output directory, Warning: Duplicated file names will be overwritten.", required=True)
+parser.add_argument("--export_npy", help="Export the audio buffer in NumPy format", action="store_true")
+args = parser.parse_args()
+
+if __name__=="__main__":
+    main(args)
+