• 전자공학회논문지B
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• 제30B권12호
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• pp.21-30
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• 1993

In this paper, we propose a connected Korean digit recohnition system employing neural networks and lexical constraints of the Korean digits. In the proposed recognition system, firstly, each frame of digit string is labelled by phoneme classification neural networks.which are trained with the reference phoneme segments extracted form an isolated digit based on the position information. And, the frame labels are combined with each other for constructing the phoneme segments. Then, these segments are combined to form a digit candidate using the digit combination rules. The digit candidate is decided based on the condition for digit decision. If the condition is not satisfied, the digit candidate is further recognized using the digit decision neural network in the next step. In our approach, the neural networks are trained with 10 isolated digits uttered by 5 male speakers. To investigate the performance of the proposed recognition system, an intensive computer simulation on the 30 connected digit strings uttered by 5 male speakers is performed. The simulation result indicates that 95.6% digit recognition rate and 82% digit string recognition rate are provided by the proposed Korean digit recognition system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.49.4-49
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• 2001

Digit recognition based on backpropagation neural networks, as an important application of pattern recognition, was attracted much attention. Although it has the advantages of parallel calculation, high error-tolerance, and learning capability, better recognition effects can only be achieved with some specific fixed format input of the digit image. Therefore, digit image preprocessing ability directly affects the accuracy of recognition. Here using Matlab software, the digit image was enhanced by resizing and neutral-rotating the extracted digit image, which improved the digit recognition capability of the backpropagation neural network under practical conditions. This method may also be helpful for recognition of other patterns with backpropagation neural networks.

• 대한음성학회지:말소리
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• 제50호
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• pp.123-137
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• 2004

In this paper, we consider the implementation of connected digit recognition system using tree structured lexicon model. To implement efficiently the fixed or variable length digit recognition system, finite state network (FSN) is required. We merge the word network algorithm that implements the FSN with lexical tree search algorithm that is used for general speech recognition system for fast search and large vocabulary systems. To find the efficient modeling of digit recognition system, we investigate some performance changes when the lexical tree search is applied.

• 대한음성학회지:말소리
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• 제46호
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• pp.77-86
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• 2003

Channel distortion and coarticulation effect in the Korean connected digit telephone speech make it difficult to achieve high performance of connected digit recognition in the telephone environment. In this paper, as a basic research to improve the recognition performance of Korean connected digit telephone speech, recognition error patterns are investigated and analyzed. Korean connected digit telephone speech database released by SiTEC and HTK system are used for recognition experiments. Both DWFBA and MRTCN methods are used for feature extraction and channel compensation, respectively. Experimental results are discussed with our findings.

• 대한음성학회지:말소리
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• 제45호
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• pp.47-61
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• 2003

In this paper, we consider the implementation of connected digit recognition system and the several approaches to improve its performance. To implement efficiently the fixed or variable length digit recognition system, finite state network (FSN) is required. We merge the word network algorithm that implements the FSN with one pass dynamic programming search algorithm that is used for general speech recognition system for fast search. To find the efficient modeling of digit recognition system, we perform some experiments along the various conditions to affect the performance and summarize the results.

• 음성과학
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• 제8권4호
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• pp.1-15
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• 2001

This paper describes the effect of new recognition unit, a unit based on semisyllable, and its post processing method. A recognition unit based on semi-syllable expresses Korean connected digit's coarticulation effect. An existing method using semi-syllable limits next models, derived from current recognized models, to make complete connected digit sequence. However, this paper uses a new method to make complete connected digit sequence. The new post-processing method recognizes isolated digit words which include digits sequence from the digit combinations being able to occur from current recognized semi-syllable sequence. This method gives an improved accuracy rate than that of existing method. This new post processing provides two advantages. 1) It corrects current mis-recognized semi-syllable unit. 2) When people say each digit, they say it without regard to saying duration.

• 대한전자공학회논문지TE
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• 제37권3호
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• pp.16-20
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• 2000

대부분의 음성인식 시스템이 확률 모델을 기반으로 한 HMM 방법을 가장 많이 사용하고 있다. 한국어 고립 전화 숫자음 인식인 경우에 만약 충분한 학습 데이터가 주어지면 HMM 방법을 사용해도 높은 인식률을 얻는다 그러나 한국어 연속 전화 숫자음 인식인 경우에 비슷하게 발음되는 전화 숫자음들에 대해서는 HMM방법이 한계를 가지고 있다. 본 논문에서는 한국어 연속 전화 숫자음 인식에서 HMM 방법의 한계를 극복하기 위해 discriminant 학습 방법을 제시한다. 실험결과는 우리가 제시한 discriminant 학습 방법이 비슷하게 발음되는 전화 숫자음들에 대해서 높은 인식률을 갖는 것을 보여준다.

• 대한음성학회지:말소리
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• 제43호
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• pp.179-188
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• 2002

Improving the recognition performance of connected digit telephone speech still remains a problem to be solved. As a basic study for it, this paper analyzes the variation of feature parameters of Korean digit telephone speech according to channel distortion. As a feature parameter for analysis and recognition MFCC is used. To analyze the effect of telephone channel distortion depending on each call, MFCCs are first obtained from the connected digit telephone speech for each phoneme included in the Korean digit. Then CMN, RTCN, and RASTA are applied to the MFCC as channel compensation techniques. Using the feature parameters of MFCC, MFCC+CMN, MFCC+RTCN, and MFCC+RASTA, variances of phonemes are analyzed and recognition experiments are done for each case. Experimental results are discussed with our findings and discussions

• 한국통신학회논문지
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• 제21권7호
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• pp.1605-1612
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• 1996

In this paper, a new approach for continuous digits recognition using the Spatio-Temporal Neural Network (STNN) is reported. The continuous seven digits are gargeted to recognize, and our initial recognition rate was 28%. In this paper, to increase the recognition rate, two methods are proposed. In the first method, to compensated the STNN's own defect as well as to emphasize the Korean digits' phonic characteristics, the starting point ofeach digit is detected using the energy and zero-crossing rate, but the ending point is detectedonly using the energy value. In this case, the seven digits recognition reate increased to 61%. Furthermore, in the second method, considering the fact that a same digit could be pronounced differently in continuously spoken environment, the number of STNNs used to represent each digit is increased from one to five. Consequently, the same digit but pronounced differently could be handled well in the new system. As a result of that, the continuously spoken seven digits recognition rate increased to 89%.

• 정보처리학회논문지A
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• 제10A권1호
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• pp.1-6
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• 2003

본 논문에서는 음절수와 모음 열 정보를 이용한 한국어 연속 숫자 인식을 제안하였다. 제안한 연속 숫자 인식기는 첫 단계로 발성된 연속 숫자 음성에서 음절수와 구간을 추출하고, 두 번째 단계로 모음 열을 인식한다. 이와 같이 인식된 모음 열 정보를 이용하여 인식 후보를 줄이게 된다. 인식후보 모델은 조음효과에 효과적으로 대처할 수 있는 CV(Consonant Vowel), VCCV, VC단위 HMM(Hidden Markov Model)을 사용하여 연속 숫자 음성인식기를 구성하였다. 실험결과 제안된 방법이 조음효과를 효과적으로 대처하고 연결 숫자 인식에 유효함을 확인하였다.