• Journal of the Korean Society of Industry Convergence
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• v.3 no.3
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• pp.229-236
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• 2000

This paper proposes on the Hanguel character CAI system using image processing. For this, firstly, the characters written by elementary school students or foreigners arc captured by CCD camera. Secondly, Recognition is accomplished by pre-processing, thinning and recognition processes. Thirdly, strokes are separated and beauty evaluation is done by matching feature value of the input image from the similarity measure function. In particular, this paper describe to define the similarity measuring function using extracted factor values after getting the beauty evaluation factor values of the consonant in the entire CAI system. Finally, the effectiveness of the proposed system is demonstrated by experiments.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.79-87
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• 2011

Although products with the fingerprint recognition system currently show a rapid growth in quantity, it is also true that efforts to consider the product quality have been lacking until now. Accordingly, this paper analyzed technological elements with domestic and foreign market situations for products with the fingerprint recognition system to develop an evaluation model to support the quality increase by evaluating aspects of product quality for the knowledge information security, identifying the level of quality and deriving directions for improvements. A model for the reliability quality evaluation was constructed that can be applied comprehensively to non-functional elements that have not been done in the existing evaluations central to the security functions by analyzing requirements for the security, performance and reliability in consideration of features on products. It is considered that this paper can make contributions to the overall quality increase for products with the knowledge information security by reflecting features and trends for the fingerprint recognition products and building a model for the reliability and evaluation to perform evaluations by product.

• Journal of the Korean Society of Food Culture
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• v.1 no.3
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• pp.219-229
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• 1986

The consumption of meat processing products in was creased in Korean recently. Morever the demand of tasted meat processing products being gradual increase in general tendency, and so we expect that in the continuing of westernizing for food life and universalizing of urvanism, the demand of meat processing products. In order to improve the marketing strategies for the meat processing industries, consummeris particular behaviors were analyzed as for consummer's recognition, recognition of problem, the evaluation of substitutional proposal, the decision of purchasing intention an purchasing behavior and the evaluation of post-purchasing to the meat processing products.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.795-808
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• 2020

Due to the poor evaluation indexes such as detection accuracy and recall rate when Yolov3 network detects aircraft in remote sensing images, in this paper, we propose a remote sensing image aircraft detection method based on machine vision. In order to improve the target detection effect, the Inception module was introduced into the Yolov3 network structure, and then the data set was cluster analyzed using the k-means algorithm. In order to obtain the best aircraft detection model, on the basis of our proposed method, we adjusted the network parameters in the pre-training model and improved the resolution of the input image. Finally, our method adopted multi-scale training model. In this paper, we used remote sensing aircraft dataset of RSOD-Dataset to do experiments, and finally proved that our method improved some evaluation indicators. The experiment of this paper proves that our method also has good detection and recognition ability in other ground objects.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.470-473
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• 2004

In this paper, the comparison of speech feature parameters for emotion recognition is studied for emotion recognition using speech signal. For this purpose, a corpus of emotional speech data recorded and classified according to the emotion using the subjective evaluation were used to make statical feature vectors such as average, standard deviation and maximum value of pitch and energy. MFCC parameters and their derivatives with or without cepstral mean subfraction are also used to evaluate the performance of the conventional pattern matching algorithms. Pitch and energy Parameters were used as a Prosodic information and MFCC Parameters were used as phonetic information. In this paper, In the Experiments, the vector quantization based emotion recognition system is used for speaker and context independent emotion recognition. Experimental results showed that vector quantization based emotion recognizer using MFCC parameters showed better performance than that using the Pitch and energy parameters. The vector quantization based emotion recognizer achieved recognition rates of 73.3％ for the speaker and context independent classification.

• Speech Sciences
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• v.7 no.3
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• pp.167-183
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• 2000

In this paper, we propose two kinds of chaos dimensions, the fuzzy correlation and fuzzy Lyapunov dimensions, for speaker recognition. The proposal is based on the point that chaos enables us to analyze the non-linear information contained in individual's speech signal and to obtain superior discrimination capability. We confirm that the proposed fuzzy chaos dimensions play an important role in enhancing speaker recognition ratio, by absorbing the variations of the reference and test pattern attractors. In order to evaluate the proposed fuzzy chaos dimensions, we suggest speaker recognition using the proposed dimensions. In other words, we investigate the validity of the speaker recognition parameters, by estimating the recognition error according to the discrimination error of an individual speaker from the reference pattern.

• ETRI Journal
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• v.45 no.4
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• pp.678-689
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• 2023

This paper describes a novel end-to-end deep generative model-based speaker recognition system using prosodic features. The usefulness of variational autoencoders (VAE) in learning the speaker-specific prosody representations for the speaker recognition task is examined herein for the first time. The speech signal is first automatically segmented into syllable-like units using vowel onset points (VOP) and energy valleys. Prosodic features, such as the dynamics of duration, energy, and fundamental frequency (F₀), are then extracted at the syllable level and used to train/adapt a speaker-dependent VAE from a universal VAE. The initial comparative studies on VAEs and traditional autoencoders (AE) suggest that the former can efficiently learn speaker representations. Investigations on the impact of gender information in speaker recognition also point out that gender-dependent impostor banks lead to higher accuracies. Finally, the evaluation on the NIST SRE 2010 dataset demonstrates the usefulness of the proposed approach for speaker recognition.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.15 no.2
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• pp.92-97
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• 2004

Background and Objectives : The purpose of this study was to examine objectively pre and post operative voice quality evaluation and intelligibility of alaryngeal voice using speech recognition program, HUVOIS. Materials and Methods : 2 laryngologists and 1 speech pathologist were evaluated 'G', 'R', 'B' in the GRBAS sclae and speech intelligibility using NTID rating scale from standard paragraph. And also acoustic estimates such as jitter, shimmer, HNR were obtained from Lx Speech Studio. Results : Speech recognition rate was not significantly different between pre and post operation for pathological vocie samples though voice quality(G, B) and acoustic values(Jitter, HNR) were significantly improved after post operation. In Alaryngeal voices, reed type electrolarynx 'Moksori' was the highest both speech intelligibility and speech recognition rate, whereas esophageal speech was the lowest. Coefficient correlation of speech intelligibility and speech recognition rate was found in alaryngeal voices, but not in pathological voices. Conclusion : Current study was not proved speech recognition program, HUVOIS during telephone program was not objective and efficient method for assisting subjective GRBAS scale.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.127-130
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• 2000

In this paper, we explore the possibility to use wavelet decomposition based on modified octave structured 5-level filter banks as a set of features for speech recognition. The HMM (Hidden Markov Model) is used as a recognizer 〔l〕. We compared the performance of the wavelet decomposition with the mel-cepstrum and LPC cepstrum. Experimental results show favorable results.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.81.2-81
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• 2002

$\textbullet$ Introduction- Concept and meaning of the emotional Recognition $\textbullet$ The feature of 4-emotions $\textbullet$ Pitch(approach) $\textbullet$ Simulator-structure, RNN(learning algorithm), evaluation function, solution search method $\textbullet$ Result