• The Journal of the Acoustical Society of Korea
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• v.16 no.3
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• pp.64-72
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• 1997

In this paper, study and experiments are performed for finding recognition unit fit which can be used in large vocabulary recognition system. Specifically, a phoneme that is currently used as recognition unit and a syllable in which Korean is well characterized are selected. From comparisons of recognition experiments, the study is performed whether a syllable can be considered as recognition unit of Korean recognition system. For report of an objective result of the comparison experiment, we collected speech data of a male speaker and processed them by hand-segmentation for phoneme boundary and labeling to construct speech database. And for training and recognition based on HMM, we used HTK (HMM Tool Kit) 2.0 of commercial tool from Entropic Co. to experiment in same condition. We applied two HMM model topologies, 3 emitting state of 5 state and 6 emitting state of 8 state, in Continuous HMM on training of each recognition unit. We also used 3 sets of PBW (Phonetically Balanced Words) and 1 set of POW(Phonetically Optimized Words) for training and another 1 set of PBW for recognition, that is "Speaker Dependent Medium Vocabulary Size Recognition." Experiments result reports that recognition rate is 95.65% in phoneme unit, 94.41% in syllable unit and decoding time of recognition in syllable unit is faster by 25% than in phoneme.

• Proceedings of the Acoustical Society of Korea Conference
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• 1987.11a
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• pp.89-92
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• 1987

In a template-matchig-based speech recognition syste, excessive weight given to perceptually unimportant spectral variations is undesirable for discriminating among acoustically similar words. By introducing a simple threshold-type nonlinearity applied to the distance metric, the word recognition performance can be improved for a vocabulary with similar sounding words, without modifying the system structure.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2
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• pp.173-179
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• 2004

Due to the insufficiency of training data in large vocabulary continuous speech recognition, similar context dependent phones can be clustered by decision trees to share the data. When the decision trees are built and used to predict unseen triphones, a phonetic question set is required. The phonetic question set, which contains categories of the phones with similar co-articulation effects, is usually generated by phonetic or linguistic experts. This knowledge-based approach for generating phonetic question set, however, may reduce the homogeneity of the clusters. Moreover, the experts must adjust the question sets whenever the language or the PLU (phone-like unit) of a recognition system is changed. Therefore, we propose a data-driven method to automatically generate phonetic question set. Since the proposed method generates the phone categories using speech data distribution, it is not dependent on the language or the PLU, and may enhance the homogeneity of the clusters. In large vocabulary speech recognition experiments, the proposed algorithm has been found to reduce the error rate by 14.3%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.2
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• pp.330-338
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• 2002

A speech recognition chip that can recognize a small vocabulary as a word-level has been designed. It is composed of EPD(Start and End-point detection) block, LPC block, DTW block and external memory interface block. It is made of 126,938 gates on 4x4mm2 area with a CMOS 0.35um TLM process. The speed of the chip varies from 5MHz to 60MHz because of its specific hardware designed for the purpose. It can compare 100,000 voices as a small vocabulary which has approximately 50∼60 frames at the clock of 5MHz and also up to 1,200,000 voices at the clock of 60MHz.

• MALSORI
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• no.49
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• pp.107-121
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• 2004

In this paper, we describe a cross-morpheme pronunciation variation model which is especially useful for constructing morpheme-based pronunciation lexicon to improve the performance of a Korean LVCSR. There are a lot of pronunciation variations occurring at morpheme boundaries in continuous speech. Since phonemic context together with morphological category and morpheme boundary information affect Korean pronunciation variations, we have distinguished phonological rules that can be applied to phonemes in within-morpheme and cross-morpheme. The results of 33K-morpheme Korean CSR experiments show that an absolute reduction of 1.45% in WER from the baseline performance of 18.42% WER was achieved by modeling proposed pronunciation variations with a possible multiple context-dependent pronunciation lexicon.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.1
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• pp.29-35
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• 2015

In this paper, we propose a intelligent retrieval system with interactive voice support. The developed system helps to find misrecognized words by using the relationship between lexical items in a sentence recognition and present the correct vocabulary. In this study, we implement a simulation system that can be proposed to determine the usefulness of the product search assistance system which offers applications. Experimental results were confirmed to correct the wrong speech recognition vocabulary in a simple user interface to help the product search.

• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.121-124
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• 1993

This paper is a study on the word recognition using neural network. A limited vocabulary, speaker independent, isolated word recognition system has been built. This system recognizes isolated word without performing segmentation, phoneme identification, or dynamic time wrapping. It needs a static pattern approach to recognize a spatio-temporal pattern. The preprocessing only includes preceding and tailing silence removal, and word length determination. A LPC analysis is performed on each of 24 equally spaced frames. The PARCOR coefficients plus 3 other features from each frame is extracted. In order to simplify a structure of neural network, we composed binary code form to decrease output nodes.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.191-203
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• 2015

In foreign language, vocabulary is the most essential and fundamental elements. Traditional language learning methods that are to understand and to memorize the English contents can only be obvious limitations. In this paper, we proposed the speaking-centered learning methods based on cognitive strategies and speech recognition considering the learner characteristics. We have designed and implemented the cognitive strategy-based speaking training system for acquisition elementary English vocabulary. We were divided into control group and the experimental group and applied to the system to analyze the learning effect. The result of Analysis, the proposed system is increased motivation and achievement of learners. In addition, the proposed system is improved an academic learning participation, Project accomplish, self-interesting and leadership skills. Through this study, we expect that students improve the ability of practical skills in speaking English.

• The Journal of the Acoustical Society of Korea
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• v.23 no.3
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• pp.242-247
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• 2004

Conventional keyword spotting systems use the connected word recognition network consisted by keyword models and filler models in keyword spotting. This is why the system can not construct the language models of word appearance effectively for detecting keywords in large vocabulary continuous speech recognition system with large text data. In this paper to solve this problem, we propose a keyword spotting system using pseudo N-gram language model for detecting key-words and investigate the performance of the system upon the changes of the frequencies of appearances of both keywords and filler models. As the results, when the Unigram probability of keywords and filler models were set to 0.2, 0.8, the experimental results showed that CA (Correctly Accept for In-Vocabulary) and CR (Correctly Reject for Out-Of-Vocabulary) were 91.1% and 91.7% respectively, which means that our proposed system can get 14% of improved average CA-CR performance than conventional methods in ERR (Error Reduction Rate).

• English Language & Literature Teaching
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• v.12 no.1
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• pp.131-158
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• 2006

The purpose of the present study is to explore an effective way of teaching English vocabulary which is geared toward improving students' English communicative competence. This study focuses on English verbs, which may be followed by patterns according to subcategorization. Learning verbs must include learning about patterns as well as meaning in order to improve the ability to use verbs receptively and productively, or communicative competence. On the basis of the language progression proposed by Willis (2003), a teaching strategy which helps learners learn English verb patterns effectively and systematically was proposed. The effect of the teaching strategy was investigated. The subjects of the experimental group who learned English verb patterns intentionally through the teaching strategy proposed by this study significantly improved themselves in the ability to use them receptively and productively. This result shows that the teaching strategy including improvisation, recognition, rehearsal, system building, exploration and consolidation is helpful to improving communicative competence.