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An Isolated Word Speech Recognition Based on Fusion of Visual and Auditory Information Usisng 30-frame/s and 24-bit Color Image
Akio OGIHARA Shinobu ASAO
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1997/08/25
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Digital Signal Processing)
speech recognition, fusion of visual and auditory, hidden Markov model, sensor fusion, full-frame (30-frame/s) and full-color (24-bit color) image,
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In the field of speech recognition, many researchers have proposed speech recognition methods using auditory information like acoustic signal or visual information like shape and motion of lips. Auditory information has valid features for speech recognition, but it is difficult to accomplish speech recognition in noisy environment. On the other side, visual information has advantage to accomplish speech recognition in noisy environment, but it is difficult to extract effective features for speech recognition. Thus, in case of using either auditory information or visual information, it is difficult to accomplish speech recognition perfectly. In this paper, we propose a method to fuse auditory information and visual information in order to realize more accurate speech recognition. The proposed method consists of two processes: (1) two probabilities for auditory information and visual information are calculated by HMM, (2) these probabilities are fused by using linear combination. We have performed speech recognition experiments of isolated words, whose auditory information (22.05kHz sampling, 8-bit quantization) and visual information (30-frame/s sampling, 24-bit quantization) are captured with multi-media personal computer, and have confirmed the validity of the proposed method.