Publication Details
Developing a Speech Activity Detection System for the DARPA RATS Program
Zhang Bing (Raytheon BBN)
Nguyen Long (Raytheon BBN)
Matsoukas Spyros (Raytheon BBN)
Zhou Xinhui (UMD)
Mesgarani Nima (UMD)
Veselý Karel, Ing., Ph.D. (DCGM FIT BUT)
Matějka Pavel, Ing., Ph.D. (DCGM FIT BUT)
speech activity detection, noisy speech
In this paper we present the SAD system developed by the Patrol team for the DARPA RATS phase 1 evaluation. The system achieves high accuracy on audio from noisy radio communication channels.
This paper describes the speech activity detection (SAD) system developed by the Patrol team for the first phase of the DARPA RATS (Robust Automatic Transcription of Speech) program, which seeks to advance state of the art detection capabilities on audio from highly degraded communication channels. We present two approaches to SAD, one based on Gaussian mixture models, and one based on multi-layer perceptrons. We show that significant gains in SAD accuracy can be obtained by careful design of acoustic front end, feature normalization, incorporation of long span features via data-driven dimensionality reducing transforms, and channel dependent modeling. We also present a novel technique for normalizing detection scores from different systems for the purpose of system combination.
@INPROCEEDINGS{FITPUB10099, author = "Tim Ng and Bing Zhang and Long Nguyen and Spyros Matsoukas and Xinhui Zhou and Nima Mesgarani and Karel Vesel\'{y} and Pavel Mat\v{e}jka", title = "Developing a Speech Activity Detection System for the DARPA RATS Program", pages = "1--4", booktitle = "Proceedings of Interspeech 2012", journal = "Proceedings of Interspeech - on-line", volume = 2012, number = 9, year = 2012, location = "Portland, Oregon, US", publisher = "International Speech Communication Association", ISBN = "978-1-62276-759-5", ISSN = "1990-9772", language = "english", url = "https://www.fit.vut.cz/research/publication/10099" }