DocumentCode :
2880977
Title :
Application of automatic speech recognition in call classification
Author :
Das, Sharmistha Sarkar ; Chan, Norman ; Wages, Danny ; Hansen, John H L
Author_Institution :
Avaya Labs., 1300 W 120-th Avenue, Westminster, CO 80234, US
Volume :
4
fYear :
2002
fDate :
13-17 May 2002
Abstract :
Call classification is the process of characterizing the audio signals encountered when a phone call is placed. The signal can be a live person, an answering machine, a call progress tone (ringback, busy, etc.), a fax modem tone or an announcement message. Call processing system uses the output of the call classifier to perform automated call routing. Traditionally, in-band signaling between communication system endpoints and users are in the form of audible tones. With the advent of technology, these signals have been augmented by synthesized and recorded human speech. A “busy tone”, for example, may be replaced by recorded speech. Traditional call classifiers, which are mainly tone detectors, have become increasingly ineffective. This paper proposes a new generation call classifier employing Automatic Speech Recognition (ASR). Modifications of the ASR paradigm are suggested to incorporate signal recognition, and results presented for two call classifier scenarios.
Keywords :
Classification algorithms; Decoding; Energy states; Markov processes; Speech; Speech recognition; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on
Conference_Location :
Orlando, FL, USA
ISSN :
1520-6149
Print_ISBN :
0-7803-7402-9
Type :
conf
DOI :
10.1109/ICASSP.2002.5745508
Filename :
5745508
Link To Document :
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