NDLI: Audio-Visual Speech Recognition with Weighted KNN-based Classification in Mandarin Database

Content Provider	IEEE Xplore Digital Library
Author	Tsang-Long Pao Wen-Yuan Liao Yu-Te Chen
Copyright Year	2007
Description	Author affiliation: Tatung Univ., Taipei (Tsang-Long Pao)
Abstract	Automatic speech recognition (ASR) by machine has been a goal and an attractive research area for past several decades. In recent years, there has been growing attractive research topic for overcoming certain audio-only recognition problems. Motivated by the multimodal nature of speech, the visual feature is considered to bring in information that dose not existing in the acoustic signal and enables improved system performance over audio-only methods. We first introduce the method for the extraction for the visual feature of the lip. In this paper, we compare three different weighting functions in weighted KNN-based classifiers to recognize ten digits, including 0 to 9, from Mandarin audio-visual speech. The classifiers studied include traditional KNN, weighted KNN, and weighted D-KNN. We also create a new audio-visual database in English and Mandarin. We will test this database for our proposed system, with some experimental results.
Starting Page	39
Ending Page	42
File Size	217436
Page Count	4
File Format	PDF
ISBN	9780769529941
DOI	10.1109/IIHMSP.2007.4457488
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-11-26
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Audio databases Training data Speech recognition Feature extraction Spatial databases Pattern recognition Data mining Visual databases Automatic speech recognition Nearest neighbor searches
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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