DocumentCode :
2581674
Title :
Detection of human speech in structured noise
Author :
Hoyt, John D. ; Wechsler, Harry
Author_Institution :
Eng. Res. Facility, Federal Bur. of Investigation, Quantico, VA, USA
fYear :
1994
fDate :
19-22 Apr 1994
Abstract :
This paper describes research to develop an efficient system that provides a binary decision as to the presence of speech in a short (one to three second) time sample of an acoustic signal. A method which is efficient and reliably detects human speech in the presence of structured noise (such as wind, music, traffic sounds, etc.) is described. Two separate algorithms were developed. The first algorithm detects the presence of speech by testing for concave and/or convex formant shapes. The second algorithm is a statistical pattern classifier utilizing radial basis function (RBF) networks with mel-cepstra feature vectors. Classification errors are not consistent across these two different methods. As a consequence, we plan to reduce our error rate by fusion of these methods
Keywords :
acoustic noise; acoustic signal detection; feedforward neural nets; pattern classification; speech processing; statistical analysis; acoustic signal; binary decision; classification errors; concave formant shapes; convex formant shapes; error rate reduction; human speech detection; mel-cepstra feature vectors; music; radial basis function networks; short time sample; statistical pattern classifier; structured noise; traffic sounds; wind; Acoustic noise; Acoustic signal detection; Acoustic testing; Error analysis; Humans; Music; Noise shaping; Shape; Speech enhancement; Telecommunication traffic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
ISSN :
1520-6149
Print_ISBN :
0-7803-1775-0
Type :
conf
DOI :
10.1109/ICASSP.1994.389676
Filename :
389676
Link To Document :
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