Unsupervised speaker adaptation for telephone call transcription

Wallace, Roy G., Thambiratnam, Kit, & Seide, Frank (2009) Unsupervised speaker adaptation for telephone call transcription. In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE, Taipei International Convention Center, Taipei, pp. 4393-4396.

View at publisher


The use of the PC and Internet for placing telephone calls will present new opportunities to capture vast amounts of un-transcribed speech for a particular speaker. This paper investigates how to best exploit this data for speaker-dependent speech recognition. Supervised and unsupervised experiments in acoustic model and language model adaptation are presented. Using one hour of automatically transcribed speech per speaker with a word error rate of 36.0%, unsupervised adaptation resulted in an absolute gain of 6.3%, equivalent to 70% of the gain from the supervised case, with additional adaptation data likely to yield further improvements. LM adaptation experiments suggested that although there seems to be a small degree of speaker idiolect, adaptation to the speaker alone, without considering the topic of the conversation, is in itself unlikely to improve transcription accuracy.

Impact and interest:

6 citations in Scopus
4 citations in Web of Science®
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

158 since deposited on 14 Jan 2010
17 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 29659
Item Type: Conference Paper
Refereed: Yes
Keywords: speaker adaptation, acoustic model adaptation, language model adaptation, unsupervised adaptation, speech recognition
DOI: 10.1109/ICASSP.2009.4960603
ISBN: 9781424423538
ISSN: 1520-6149
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Natural Language Processing (080107)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Institutes > Information Security Institute
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2009 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 14 Jan 2010 00:28
Last Modified: 10 Aug 2011 17:49

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page