Directory assistance: learning user formulations for business listings

Author

Popovici, C. ; Andorno, M. ; Laface, P. ; Fissore, L. ; Nigra, M. ; Vair, C.

Author_Institution

Politecnico di Torino, Italy

fYear

2001

fDate

2001

Firstpage

248

Lastpage

251

Abstract

One of the main problems in automatic directory assistance (DA) for business listings is that customers formulate their requests for the same listing with a great variability. We show that an automatic approach allows the detection, from field data, of user formulations that were not foreseen by the designers, and that they can be added, as variants, to the denominations already included in the system to reduce its failures.

Keywords

learning (artificial intelligence); speech recognition; speech-based user interfaces; Loquendo; Telecom Italia; automatic directory assistance; business listings; formulation variants; isolated word recognition; large vocabulary; speech recognition; user formulation detection; Books; Databases; Decoding; Face recognition; Hidden Markov models; Humans; Isolation technology; Speech; Telecommunications; Vocabulary;

fLanguage

English

Publisher

ieee

Conference_Titel

Automatic Speech Recognition and Understanding, 2001. ASRU '01. IEEE Workshop on

Print_ISBN

0-7803-7343-X

Type

conf

DOI

10.1109/ASRU.2001.1034634

Filename

1034634

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=381277