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