Multivariate speech activity dector based on the syllable rate

David C. Smith; Jeffrey N. Townsend; Douglas J. Nelson

doi:10.1117/12.325725

2 October 1998 Multivariate speech activity dector based on the syllable rate

David C. Smith, Jeffrey N. Townsend, Douglas J. Nelson

Proceedings Volume 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII; (1998) https://doi.org/10.1117/12.325725
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

Computationally efficient algorithms which perform speech activity detection have significant potential economic and labor saving benefit, by automating an extremely tedious manual process. In many applications, it is desirable to extract intervals of speech which are obtained by segments of other signal types. In the past, algorithms which successfully discriminate between speech and one specific other signal type have been developed. Frequently, these algorithms fail when the specific non-speech signal is replaced by a different non-speech discrimination problem. Typically, several signal specific discriminators are blindly combined with predictable negative results. Moreover, when a large number of discriminators are involved, dimensions reduction is achieved using Principal Components, which optimally compresses signal variance into the fewest number of dimensions. Unfortunately, these new coordinates are not necessarily optimal for discrimination. In this paper we apply graphical tools to determine a set of discriminators which produce excellent speech vs. non-clustering, thereby eliminating the guesswork in selecting good feature vectors. This cluster structure provides a basis for a general multivariate speech vs. non-speech discriminator, which compares very favorably with the TALKATIVE speech extraction algorithm.

Citation Download Citation

David C. Smith, Jeffrey N. Townsend, and Douglas J. Nelson "Multivariate speech activity dector based on the syllable rate", Proc. SPIE 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, (2 October 1998); https://doi.org/10.1117/12.325725

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Detection and tracking algorithms

Sensors

Algorithm development

Interference (communication)

Signal detection

Signal to noise ratio

Signal processing

Show All Keywords

Keywords/Phrases

Search In:

Publication Years