• Journal of Digital Convergence
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• v.11 no.6
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• pp.137-142
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• 2013

Speech recognition system is input of inaccurate vocabulary by feature extraction case of recognition by appear result of unrecognized or similar phoneme recognized. Therefore, in this paper, we propose a speech recognition error correction method using phoneme similarity rate and reliability measures based on the characteristics of the phonemes. Phonemes similarity rate was phoneme of learning model obtained used MFCC and LPC feature extraction method, measured with reliability rate. Minimize the error to be unrecognized by measuring the rate of similar phonemes and reliability. Turned out to error speech in the process of speech recognition was error compensation performed. In this paper, the result of applying the proposed system showed a recognition rate of 98.3%, error compensation rate 95.5% in the speech recognition.

• Proceedings of the KSPS conference
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• 1997.07a
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• pp.142-143
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• 1997

The purpose of this paper is to assess the psychological status of the phoneme, syllable, and various postulated subsyllabic units in Korean by applying the Sound Similarity Judgment (SSJ) task, to compare the results with those in English, and to discuss the advantage and disadvantage of the SSJ task as a tool for linguistic research. In Experiment 1, 30 subjects listened to pairs of 56 eve words which were systematically varied from 'totally different' (e.g., pan-met) to 'identical' (e.g., pan-pan). Subjects were then asked to rate sound similarity of each pair on a 10-point scale. Not very surprisingly, there was a strong correlation between the number of phonemic segments matched and the similarity score provided by the subjects. This result was in accord with the previous results from English (e.g., Vitz & Winkler, 1973; Derwing & Nearey, 1986) and supported the assumption that the phoneme is the basic phonological unit in Korean and English. However, there were sharply contrasting results between the two languages. When the pairs shared two phonemes (e.g., pan-pat; pan-pen; pan-man), the pairs sharing the fIrst two phonemes were judged significantly more similar than the other two types of pairs. Quite to the contrary, in the comparable English experiments, the pairs sharing the last two phonemes were judged significantly more similar than the other two types of pairs. Experiment 2 was designed to conflrm the results of Experiment 1 by controlling the 'degree' of similarity between phonemes. For example, the pair pan-pam can be judged more similar than the pair pan-nan, although both pairs share the same number of phonemes. This could be interpreted either as confirming the result of Experiment 1 or as the fact that /n/ is more similar to /m/ than /p/ is to /n/ in terms of shared number of distinctive features. The results of Experiment 2 supported the former interpretation. Thus, the results of both experiments clearly showed that, although the 'number' of matched phonemes is the important predictor in judging sound similarity of monosyllabic pairs of both languages, the 'position' of the matched phonemes exerts a different influence in judging sound similarity in the two languages. This contrasting set of results may provide interesting implications for the internal structure of the syllable in the two languages.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.9
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• pp.8-16
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• 1992

This paper presents a method which can recognized the Handwritten Korean characters by using a Context-Free Grammar. The input characters are thinned in order to dwindle the mount of data, the thinned characters are converted into one-dimension strings according to six-forms. when the point of contact among phonemes is found, two phonemes are seperated respectively by marking the index mark (\) at the points. The Context-Free Grammar to input characters is classified into group grammars concerning the similarity of phonemes, input characters are parsed by making use of the Pushdown automata method. As the bent parts in the Handwritten characters are found frequently, We try to correct the bent parts by using the parsing distance measure, which recognize characters according to minium value caused by measuring the weight distance between two sentences. In this experiment, the recognition rate shows 93.8% to 275 Handwritten Korean characters.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2E
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• pp.14-23
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• 1996

This paper is a on the neural network to recognize the phonemes, the weight initialization to reduce learning speed, and LR parser for continuous speech recognition. The neural network spots the phonemes in continuous speech and LR parser parses the output of neural network. The whole phonemes recognized in neural network are divided into several groups which are grouped by the similarity of phonemes, and then each group consists of neural network. Each group of neural network to recognize the phonemes consisits of that recognize the phonemes of their own group and VGNN(Verify Group Neural Network) which judges whether the inputs are their own group or not. The weights of neural network are not initialized with random values but initialized from learning data to reduce learning speed. The LR parsing method applied to this paper is not a method which traces a unique path, but one which traces several possible paths because the output of neural network is not accurate. The parser processes the continuous speech frame by frame as accumulating the output of neural network through several possible paths. If this accumulated path-value drops below the threshold value, this path is deleted in possible parsing paths. This paper applies the continuous speech recognition system to the threshold value, this path is deleted in possible parsing paths. This paper applies the continuous speech recognition system to the continuous Korea digits recognition. The recognition rate of isolated digits is 97% in speaker dependent, and 75% in speaker dependent. The recognition rate of continuous digits is 74% in spaker dependent.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.3-8
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• 1999

Previous variable vocabulary speech recognition systems with context-independent acoustic modeling, could not represent the effect of neighboring phonemes. To solve this problem, we use allophone-based context-dependent acoustic model. This paper describes the method to improve acoustic model of the system effectively. Acoustic model is improved by using allophone clustering technique that uses entropy as a similarity measure and the optimal allophone model is generated by changing the number of allophones. We evaluate performance of the improved system by using Phonetically Optimized Words(POW) DB and PC commands(PC) DB. As a result, the allophone model composed of six hundreds allophones improved the recognition rate by 13% from the original context independent model m POW test DB.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.424-433
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• 2015

This study tried to investigate the differences between auditory preferences for a discrimination study of minimal pairs with the different onset and the same nucleus of a syllable on the basis of articulator-distance in case of Korean infants and toddlers. As a result we found a main effect for articulator-distance and age but not an effect according to the types of phonation especially in terms of tense. Former results are line with the previous studies having reported the order of consonants acquisition based on the places of articulation suggesting that more sensitive responses for the contiguous and different phonemes may lead earlier acquisition for the same place of articulation of the speech sounds. Specifically, bilabial soudns are followed by alveolar and palatal sounds in order. The latter results also showed that tense consonants got a high rate of recognition beside lax consonants according to the age and sex.