New Features for Speech Activity Detection

Punnoose A K


´╗┐This paper discusses two new features for speech activity detection(SAD), using a multi-layer perceptron(mlp) trained to predict phoneme from acoustic features. The first feature is based on the difference between speech and noise histogram of certain phonemes. A scoring mechanism is formulated to score the softmax probabilities of the frames of a phoneme. The second feature is based on the correlation between softmax probabilities of the edge frames for certain phoneme transitions. A probabilistic approach is formulated to score the phoneme transition. Relevant datasets are used to prove the robustness of the proposed features in terms of speech activity detection.


 DOI: 10.21437/SMM.2019-6

Cite as: K, P.A. (2019) New Features for Speech Activity Detection. Proc. SMM19, Workshop on Speech, Music and Mind 2019, 26-30, DOI: 10.21437/SMM.2019-6.


@inproceedings{K2019,
  author={Punnoose A K},
  title={{New Features for Speech Activity Detection}},
  year=2019,
  booktitle={Proc. SMM19, Workshop on Speech, Music and Mind 2019},
  pages={26--30},
  doi={10.21437/SMM.2019-6},
  url={http://dx.doi.org/10.21437/SMM.2019-6}
}