Cross database training of audio-visual hidden Markov models for phone recognition

Kalantari, Shahram, Dean, David, Ghaemmaghami, Houman, Sridharan, Sridha, & Fookes, Clinton (2015) Cross database training of audio-visual hidden Markov models for phone recognition. In Proceedings of the 16th Annual Conference of the International Speech Communication Association, Interspeech 2015, International Speech Communication Association, Maritim International Congress Center, Dresden, Germany, pp. 553-557.

View at publisher

Abstract

Speech recognition can be improved by using visual information in the form of lip movements of the speaker in addition to audio information. To date, state-of-the-art techniques for audio-visual speech recognition continue to use audio and visual data of the same database for training their models. In this paper, we present a new approach to make use of one modality of an external dataset in addition to a given audio-visual dataset. By so doing, it is possible to create more powerful models from other extensive audio-only databases and adapt them on our comparatively smaller multi-stream databases. Results show that the presented approach outperforms the widely adopted synchronous hidden Markov models (HMM) trained jointly on audio and visual data of a given audio-visual database for phone recognition by 29% relative. It also outperforms the external audio models trained on extensive external audio datasets and also internal audio models by 5.5% and 46% relative respectively. We also show that the proposed approach is beneficial in noisy environments where the audio source is affected by the environmental noise.

Impact and interest:

0 citations in Scopus
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:

26 since deposited on 27 Jul 2015
9 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: 86035
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Phone recognition, synchronous hidden Markov model, fused hmm adaptation, cross database training
ISSN: 1990-9770
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 [please consult the authors]
Deposited On: 27 Jul 2015 22:34
Last Modified: 24 Sep 2015 14:02

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page