• Speech Sciences
• /
• v.10 no.2
• /
• pp.27-33
• /
• 2003

Bimodal speech recognition based on lip reading has been studied as a representative method of speech recognition under noisy environments. There are three integration methods of speech and lip modalities as like direct identification, separate identification and dominant recording. In this paper we evaluate the robustness of lip reading methods under the assumption that lip parameters are estimated with errors. We show that the dominant recording approach is more robust than other methods through lip reading experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.13 no.3
• /
• pp.164-170
• /
• 2013

Recent years have been higher demands for automatic speech recognition (ASR) systems that are able to operate robustly in an acoustically noisy environment. This paper proposes an improved product hidden markov model (HMM) used for bimodal speech recognition. A two-dimensional training model is built based on dependently trained audio-HMM and visual-HMM, reflecting the asynchronous characteristics of the audio and video streams. A weight coefficient is introduced to adjust the weight of the video and audio streams automatically according to differences in the noise environment. Experimental results show that compared with other bimodal speech recognition approaches, this approach obtains better speech recognition performance.

• Speech Sciences
• /
• v.8 no.3
• /
• pp.123-132
• /
• 2001

In recent years research on HCI technology has been very active and speech recognition is being used as its typical method. Its recognition, however, is deteriorated with the increase of surrounding noise. To solve this problem, studies concerning the multimodal HCI are being briskly made. This paper describes automated lipreading for bimodal speech recognition on the basis of image- and speech information. It employs audio-visual DB containing 1,074 words from 70 voice and tri-viseme as a recognition unit, and state tied HMM as a recognition model. Performance of automated recognition of 22 to 1,000 words are evaluated to achieve word recognition of 60.5% in terms of 22word recognizer.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.1
• /
• pp.45-51
• /
• 2022

Sound quality evaluation is one of the psychoacoustic methods to measure subjective judgements for sound color. The purpose of this study is to investigate sound quality benefits of bimodal users by comparing sound quality scores between bimodal hearing condition and unilateral cochlear implant(CI) condition as a preliminary study. Thirteen bimodal users and seven unilateral CI users were participated in this study. Audiologists performed pure tone and speech audiometry and measured functional gain and real-ear insertion gain. Subjective assessment of sound quality was followed with four sounds including violin sound, male and female voices, and refrigerator noise. Participants judged the sound quality with six sound quality index. Bimodal users showed mean 0.8 points more sound quality improvements in bimodal condition than unilateral CI condition. Group comparison between bimodal and unilateral CI users showed no differences. A follow-up study of sound quality tools and methods should be considered to evaluate subjective bimodal benefits of cochlear implant users.

• Proceedings of the KSPS conference
• /
• 2002.11a
• /
• pp.205-208
• /
• 2002

Bimodal speech recognition based on lip reading has been studied as a representative method of speech recognition under noisy environments. There are three integration methods of speech and lip modalities as like direct identification, separate identification and dominant recording. In this paper we evaluate the robustness of lip reading methods under the assumption that lip parameters are estimated with errors. We show that the dominant recording approach is more robust than other methods with lip reading experiments. Also, a measure of lip parameter degradation is proposed. This measure can be used in the determination of weighting values of video information.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.6
• /
• pp.51-56
• /
• 2001

Recent researches have been focusing on jointly using lip motions and speech for reliable speech recognitions in noisy environments. To this end, this paper proposes the method of combining the visual speech recognizer and the conventional speech recognizer with each output properly weighted. In particular, we propose the method of autonomously determining the weights, depending on the amounts of noise in the speech. The correlations between adjacent speech samples and the residual errors of the LPC analysis are used for this determination. Simulation results show that the speech recognizer combined in this way provides the recognition performance of 83 ％ even in severely noisy environments.

• The Journal of the Acoustical Society of Korea
• /
• v.22 no.1
• /
• pp.28-34
• /
• 2003

Recent researches have been focusing on jointly using lip motions (i.e. visual speech) and speech for reliable speech recognitions in noisy environments. This paper also deals with the method of combining the result of the visual speech recognizer and that of the conventional speech recognizer through putting weights on each result: the paper proposes the method of determining proper weights for each result and, in particular, the weights are autonomously determined, depending on the amounts of noise in the speech and the image quality. Simulation results show that combining the audio and visual recognition by the proposed method provides the recognition performance of 84% even in severely noisy environments. It is also shown that in the presence of blur in images, the newly proposed weighting method, which takes the blur into account as well, yields better performance than the other methods.

• The Journal of the Acoustical Society of Korea
• /
• v.18 no.4
• /
• pp.31-37
• /
• 1999

A bimodal speech recognition using visual and audio information has been proposed and researched to improve the performance of ASR(Automatic Speech Recognition) system in noisy environments. The integration method of two modalities can be usually classified into an early integration and a late integration. The early integration method includes a method using a fixed weight of lip parameters and a method using a variable weight according to speech SNR information. The 4 late integration methods are a method using audio and visual information independently, a method using speech optimal path, a method using lip optimal path and a way using speech SNR information. Among these 6 methods, the method using the fixed weight of lip parameter showed a better recognition rate.

• Journal of KIISE:Software and Applications
• /
• v.31 no.4
• /
• pp.403-410
• /
• 2004

Bimodal speech recognition systems have been proposed for enhancing recognition rate of ASR under noisy environments. Visual feature extraction is very important to develop these systems. To extract visual features, it is necessary to detect exact lip position. This paper proposed the method that detects a lip position using color similarity model and SVM. Face/Lip color distribution is teamed and the initial lip position is found by using that. The exact lip position is detected by scanning neighbor area with SVM. By experiments, it is shown that this method detects lip position exactly and fast.

• The Journal of the Acoustical Society of Korea
• /
• v.18 no.3
• /
• pp.68-72
• /
• 1999

The choice of parameters from various lip information and the robustness of extracting lip parameters play important roles in the performance of bimodal speech recognition system. In this paper, lip parameters are extracted by using an automatic extraction algorithm and inner lip parameters effect on the recognition rate more than outer lip parameters. Compared with a manual extraction algorithm, the automatic extraction method is evaluated about its robustness.