https://github.com/shammur/pyvad
A simple VAD pipeline based on pyAudioAnalysis
https://github.com/shammur/pyvad
Last synced: about 2 months ago
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A simple VAD pipeline based on pyAudioAnalysis
- Host: GitHub
- URL: https://github.com/shammur/pyvad
- Owner: shammur
- License: mit
- Created: 2020-09-17T06:25:06.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-10-04T07:41:29.000Z (over 4 years ago)
- Last Synced: 2025-03-24T06:03:57.743Z (2 months ago)
- Language: Python
- Size: 655 KB
- Stars: 4
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# pyVAD
A simple VAD pipeline based on pyAudioAnalysis
# Running Simple Speech Segmentation
To run the please use python version 3.7, install dependencies
To install the requirements:
```
pip install -r requirements.txt
pip install -r requirements_pyAudio.txt #if needed
```
The pipeline can be used in two ways, either using by giving a maximum duration of segments (merging small segments) or as it is given by the silence based segmentation.
##For getting raw-segmentation (based on silence boundary) use:
`python src/vad_simple.py VAD_simple -i $INPUT_FOLDER -o $OUTPUT_FOLDER --smoothing $SMOOTHING_FACTOR --weight $WEIGHT_FACTOR --classifier /alt/asr/shchowdhury/vad/vad_simple_pipeline/models/svm_rbf_sm`
here: INPUT_FOLDER = folder that has the original audio,
e.g.
$WORK_PATH"/data/"
ls data -->
`prep_AToUwCP1wHY.wav prep_hsjH22Mp6xo.wav prep_M7fecxjjmL4.wav`
OUTPUT_FOLDER = location where one folder per audio (prep_AToUwCP1wHY) is created. Inside prep_AToUwCP1wHY/
segmented audios along with `segments` and `segment_details` file is created
e.g
ls data_out_merged/
`prep_AToUwCP1wHY prep_czhUGrb1Rms`
ls data_out_merged/prep_AToUwCP1wHY
`prep_AToUwCP1wHY_993.550_1003.150.wav segments`
File format for `segments` file:
e.g.
prep_AToUwCP1wHY_25.100_34.400 prep_AToUwCP1wHY 25.100 34.400
##For getting merged-segmentation (based on silence boundary and a threshold for maximum duration) use:
`python src/vad_simple.py VAD_simple_merged -i $INPUT_FOLDER -o $OUTPUT_FOLDER --smoothing $SMOOTHING_FACTOR --weight $WEIGHT_FACTOR --classifier /alt/asr/shchowdhury/vad/vad_simple_pipeline/models/svm_rbf_sm -t 10.0`
Options:
`For VAD_simple
"VAD_simple" : "Remove silence segments from a recording in the filder")
-i, "--input", required=True, help="input audio file location"
-o, "--output", required=True, help="output audio file location")
-w, "--weight", type=float, default=0.5, help="weight factor in (0, 1)"
--classifier", required=True, help="Classifier to use (filename)"
-s, "--smoothing", type=float, default=1.0,
help="smoothing window size in seconds.")
For VAD_simple_merged:
-i, "--input", required=True, help="input audio file location"
-o, "--output", required=True, help="output audio file location"
-w, "--weight", type=float, default=0.5, help="weight factor in (0, 1)
--classifier", required=True, help="Classifier to use (filename)"
-t, --threshold, type=float, default=10.0
-s, "--smoothing", type=float, default=1.0,
help="smoothing window size in seconds.")
-t, "--threshold", type=float, default=10.0, help="max segment size in seconds.")`