• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.784-788
• /
• 2008

In this research, we propose a remote speech input unit, a new method of user-friendly speech input in speech recognition system. We focused the user friendliness on hands-free and microphone independence in speech recognition applications. Our module adopts two algorithms, the automatic speech detection and speech enhancement based on the microphone array-based beamforming method. In the performance evaluation of speech detection, within-200msec accuracy with respect to the manually detected positions is about 97percent under the noise environments of 25dB of the SNR. The microphone array-based speech enhancement using the delay-and-sum beamforming algorithm shows about 6dB of maximum SNR gain over a single microphone and more than 12% of error reduction rate in speech recognition.

• MALSORI
• /
• no.52
• /
• pp.161-169
• /
• 2004

This paper describes the automated call routing for train ticket reservation aid system based on speech recognition. We focus on the task of automatically routing telephone calls based on user's fluently spoken response instead of touch tone menus in an interactive voice response system. Vector-based call routing algorithm is investigated and mapping table for key term is suggested. Korail database collected by KT is used for call routing experiment. We evaluate call-classification experiments for transcribed text from Korail database. In case of small training data, an average call routing error reduction rate of 14% is observed when mapping table is used.

• Phonetics and Speech Sciences
• /
• v.4 no.3
• /
• pp.95-101
• /
• 2012

In this paper, we introduce the automatic speaker identification system 'SPO(Supreme Prosecutors Office) Verifier'. SPO Verifier is a GMM(Gaussian mixture model)-UBM(universal background model) based automatic speaker recognition system and has been developed using Korean speakers' utterances. This system uses a channel compensation algorithm to compensate recording device characteristics. The system can give the users the ability to manage reference models with utterances from various environments to get more accurate recognition results. To evaluate the performance of SPO Verifier on Korean speakers, we compared this system with one of the most widely used commercial systems in the forensic field. The results showed that SPO Verifier shows lower EER(equal error rate) than that of the commercial system.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.15 no.4
• /
• pp.520-530
• /
• 1996

In this study, the artificial defects in rotary compressor are classified using pattern recognition of acoustic emission signal. For this purpose the computer program is developed. The neural network classifier is compared with the statistical classifier such as the linear discriminant function classifier and empirical Bayesian classifier. It is concluded that the former is better. It is possible to acquire the recognition rate of above 99% by neural network classifier.

• Proceedings of the IEEK Conference
• /
• 2001.06d
• /
• pp.175-178
• /
• 2001

This paper proposes a novel human-computer interaction system for the disabled using recognition of face direction. Face direction is recognized by comparing positions of center of gravity between face region and facial features such as eyes and eyebrows. The face region is first selected by using color information, and then the facial features are extracted by applying a separation filter to the face region. The process speed for recognition of face direction is 6.57frame/sec with a success rate of 92.9% without any special hardware for image processing. We implement human-computer interaction system using screen menu, and show a validity of the proposed method from experimental results.

• 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.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.1
• /
• pp.81-87
• /
• 1994

This paper describes the recognition of the printed Hanguel(Korean Character) using Neural Network. In this study, Neural network is used in only specific classification. Hanguel is classified globally by using template matching. Neural network is learned using the segmented grapheme. The grapheme of Hanguel is segmented using the structural method. Neural network is constructed, which is corresponded to the kind and the shape of graphemes. Each neural network is multi layer perceptron. The learning algorithm is the modified error back propagation using descending epsilon method. With five test character sets, the recognition rate of 94.95% is obtained.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.1223-1226
• /
• 1998

The pre-emephasis filter as the conventional method emphasizes all components of high frequency that reflects the speaker characteristics. However this filter don't show the auditory characteristics of speaker's speech. In order to emphasize the perceptual characteristics, we propose the speaker recognition system that uses the perceptual weighting as the preprocessor because the Auditory characteristic of human is sensitive to the formant peaks. This filter has the characteristcs that both deemphasizes the low-formants and emphasizes the high formants. As a result of the proposed method, we improve the total recognition rate 1.7% better than the conventional method.

• Proceedings of the IEEK Conference
• /
• 2000.09a
• /
• pp.327-330
• /
• 2000

In this paper, we describe an intelligent method to detect types of vehicles using Support Vector Machines focused to the Intelligent Transportation System (ITS) applications such as in the CCD based Electronic Toll Collection System (ETCS). This algorithm can be used the various fields of ITS applications. Support Vector Machines employed in this paper has been recently proposed as a very effective method for 3D image recognition. And our proposed feature extraction method using the singluar values that directly come from pixels at input images. Consequently, The low calculation load and the high recognition rate in spite of image rotation and various noises are one of merits of proposed method.

• Journal of Biomedical Engineering Research
• /
• v.22 no.3
• /
• pp.217-222
• /
• 2001

This paper proposes the new method based on fuzzy logic which recognizes between normal, and abnormal(two types of abnormal : follicular neoplastic, and papillary neoplastic) of thyroid gland cells from pre-obtained 16 feature parameters of image data. This paper applies the genetic algorithms to obtain the dominant feature parameters which have a great influence on discrimination between normal and abnormal cells. This paper shows the effectiveness of proposed method to 240 thyroid gland cells(60 normal cells, 120 follicular neoplastic cells and 60 papillary neoplastic cells) and new dominant feature parameters obtained by genetic algorithms. As a consequence of using the proposed method, average recognition rate of 88.75 % was obtained.