• 말소리와 음성과학
• /
• 제8권2호
• /
• pp.23-30
• /
• 2016

This paper describes some implementation schemes of CNN in view of mini-batch DNN training for efficient second order optimization. This uses same procedure updating parameters of DNN to train parameters of CNN by simply arranging an input image as a sequence of local patches, which is actually equivalent with mini-batch DNN training. Through this conversion, second order optimization providing higher performance can be simply conducted to train the parameters of CNN. In both results of image recognition on MNIST DB and syllable automatic speech recognition, our proposed scheme for CNN implementation shows better performance than one based on DNN.

• 디지털산업정보학회논문지
• /
• 제8권1호
• /
• pp.29-40
• /
• 2012

A challenging research issue that has been one of growing importance to those working in human-computer interaction are to endow a machine with an emotional intelligence. Thus, emotion recognition technology plays an important role in the research area of human-computer interaction, and it allows a more natural and more human-like communication between human and computer. In this paper, we propose the multimodal emotion recognition system using face and speech to improve recognition performance. The distance measurement of the face-based emotion recognition is calculated by 2D-PCA of MCS-LBP image and nearest neighbor classifier, and also the likelihood measurement is obtained by Gaussian mixture model algorithm based on pitch and mel-frequency cepstral coefficient features in speech-based emotion recognition. The individual matching scores obtained from face and speech are combined using a weighted-summation operation, and the fused-score is utilized to classify the human emotion. Through experimental results, the proposed method exhibits improved recognition accuracy of about 11.25% to 19.75% when compared to the most uni-modal approach. From these results, we confirmed that the proposed approach achieved a significant performance improvement and the proposed method was very effective.

• 음성과학
• /
• 제12권3호
• /
• pp.91-102
• /
• 2005

This study investigated to the effects of a mental image drawing in RHD patients with left neglect. Three subjects participated in this study. All subjects were right handed and native speaker of korean. In task 1, the patients were presented with visual stimulus card directly above the response sheet and were asked to draw the picture. In task 2, they were presented with items auditorily and asked to draw the picture(mental image drawing). In all experimental conditions, there was no response time limit. The results showed that the subjects showed left neglect leaving some space on the left side in task 1. And the picture was drawn the left side from the right in direction. However, the neglect disappeared in task 2. And the picture was drawn the right side from the left in direction. The results of the present study suggested that a mental image drawing technique can be effective in treating individuals who exhibit left neglect. Also, the picture direction showed that the korean normality was same.

• 음성과학
• /
• 제12권1호
• /
• pp.135-142
• /
• 2005

An important aspect of video indexing is the ability to segment video into meaningful segments, i.e., content-based video segmentation. Since the audio signal in the sound track is synchronized with image sequences in the video program, a speech signal in the sound track can be used to segment video into meaningful segments. In this paper, we propose a new approach to content-based video segmentation. This approach uses closed caption to construct a recognition network for speech recognition. Accurate time information for video segmentation is then obtained from the speech recognition process. For the video segmentation experiment for TV news programs, we made 56 video summaries successfully from 57 TV news stories. It demonstrates that the proposed scheme is very promising for content-based video segmentation.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
• /
• pp.5-8
• /
• 2001

The computer programs based upon graphic user interface(GUI) became commonplace with the advance of computer technology. Nevertheless, programs for the visually-handicapped have still remained at the level of TTS(text to speech) programs and this prevents many visually-handicapped from enjoying the pleasure and convenience of the information age. This paper is, paying attention to the importance of character recognition in images, about the configuration of the system that converts text in the image selected by a user to the speech by extracting the character part, and carrying out character recognition.

• 음성과학
• /
• 제8권3호
• /
• 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.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
• /
• pp.1347-1351
• /
• 1987

This thesis aims at studying laplacian pyramid vector quantization which keeps a simple compression algorithm and stability against various kinds of image data. To this end, images are devied into two groups according to their statistical characteristics. At 0.860 bits/pixel and 0.360 bits/pixel respectively, laplacian pyramid vector quantization is compared to the existing spatial domain vector quantization and transform coding under the same condition in both objective and subjective value. The laplacian pyramid vector quantization is much more stable against the statistical characteristics of images than the existing vector quantization and transform coding.

• 말소리와 음성과학
• /
• 제9권4호
• /
• pp.59-67
• /
• 2017

Regardless of their intention, listeners tend to assess speakers' personalities based on the sounds of the speech they hear. Assessment criteria, however, have not been fully investigated to indicate whether there is any relationship between the acoustic cue of produced speech sounds and perceived personality impression. If properly investigated, the potential relationship between these two will provide crucial insights on the aspects of human communications and further on human-computer interaction. Since human communications have distinctive characteristics of simultaneity and complexity, this investigation would be the identification of minimum essential factors among the sounds of speech and perceived personality impression. The purpose of this study, therefore, is to identify significant associations between the speech sounds and perceived personality impression of speaker by the listeners. Twenty eight subjects participated in the experiment and eight acoustic parameters were extracted by using Praat from the recorded sounds of the speech. The subjects also completed the Neo-five Factor Inventory test so that their personality traits could be measured. The results of the experiment show that four major factors(duration average, pitch difference value, pitch average and intensity average) play crucial roles in defining the significant relationship.

• 대한음성학회:학술대회논문집
• /
• 대한음성학회 2002년도 11월 학술대회지
• /
• pp.191-194
• /
• 2002

Lip-reading technology that is studied them is used to compensate speech recognition degradation in noise environment in bi-modal's form. The most important thing is that search for correct lips area in this lip-reading. But, it is hard to forecast stable performance in dynamic environment. Used RASTA filter that show good performance to remove noise in the speech to compensate. This filter shows that improve performance of using time domain of digital filter. To this experiment observes performance of speech recognition only using image information, service chooses possible 22 words and did recognition experiment in car. We used hidden Markov model by speech recognition algorithm to compare this words' recognition performance.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송공학회 2009년도 IWAIT
• /
• pp.441-445
• /
• 2009

We have developed a real-time software tool to extract a speech feature vector whose time sequences consist of three groups of vector components; the phonetic/acoustic features such as formant frequencies, the phonemic features as outputs on neural networks, and some distances of Japanese phonemes. In those features, since the phoneme distances for Japanese five vowels are applicable to express vowel articulation, we have designed a switch, a volume control and a color representation which are operated by pronouncing vowel sounds. As examples of those vowel interface, we have developed some speech training tools to display a image character or a rolling color ball and to control a cursor's movement for aurally- or vocally-handicapped children. In this paper, we introduce the functions and the principle of those systems.