MLECO-2354 MLECO-2355 MLECO-2356: Moving noise reduction to public repository
* Use RNNoise model from PMZ
* Add Noise reduction use-case
Signed-off-by: Richard burton <richard.burton@arm.com>
Change-Id: Ia8cc7ef102e22a5ff8bfbd3833594a4905a66057
diff --git a/scripts/py/rnnoise_dump_extractor.py b/scripts/py/rnnoise_dump_extractor.py
new file mode 100644
index 0000000..947a75a
--- /dev/null
+++ 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)
+