Title :
Recognizing connected digits in a natural spoken dialog
Author_Institution :
AT&T Labs.-Res., Florham Park, NJ, USA
Abstract :
This paper addresses the general problem of connected digit recognition in the telecommunication environment. In particular, we focus on a task of recognizing digits when embedded in a natural spoken dialog. Two different design strategies are investigated: keyword detection of word spotting, and large-vocabulary continuous speech recognition. We characterize the potential benefits and describe the main components of each design method, including acoustic and language modeling, training and utterance verification. Experimental results on a subset of a database that includes customers responses to the open-ended prompt “How may I help you?” are presented
Keywords :
acoustic signal processing; natural languages; speech recognition; acoustic modeling; connected digit recognition; customers responses; design strategies; experimental results; keyword detection; language modeling; large-vocabulary continuous speech recognition; natural spoken dialog; telecommunication environment; training; utterance verification; word spotting; Acoustic signal detection; Background noise; Credit cards; Databases; Degradation; Design methodology; Error analysis; Speech recognition; Telephony; World Wide Web;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
Conference_Location :
Phoenix, AZ
Print_ISBN :
0-7803-5041-3
DOI :
10.1109/ICASSP.1999.758085