Voice Activity Detection: In this first assignment, we will create a dataset that simulates speech in every-day scenarios. We train a classifier on this dataset for distinguishing voiced from non-voiced sections, a task called voice activity detection, VAD for short. This, of course, requires a ground truth in terms of VAD annotations.
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Updated Readme and re-named FramLevelAnnotation_weighted39D.py to input_and_target_dataset_mfcc_26D.py and other minor changes.
f9c81f1View on GitHubAdded FramelevelAnnotation_weighted_39D.py and estimate_liblinear_svm_parameters.py
b06fae4View on GitHubMerge branch 'master' of github.com:netankit/AudioMLProject1
d057cc9View on GitHubAdded classification_report.py output and usage to readme
07e30a9View on GitHub