• Proceedings of the Acoustical Society of Korea Conference
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• 1995.06a
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• pp.65-68
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• 1995

이 논문은 현재 주식시장에 상장되어 있는 약 700개 회사의 현재주가를 음성인식을 이용하여 검색할 수 있는 대어휘, 화자독립, 단어독립 음성인식 시스팀의 운용자를 위한 운용관리 시스팀에 대해 기술하였다. KT-STOCK은 시스팀의 음성안내에 따라 사용자가 전화기에 상장회사 이름을 말하면, 이 시스팀은 그 회사의 현재 증권정보를 말해준다. 이 시스팀의 운용관리 시스팀은 주식시장에 상장된 종목의 변화에 따라서 인식대상 단어를 추가하거나 삭제, 조회할 때 그 처리를 용이하게 할 수 있도록 구현되었다.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.629-632
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• 2000

In this paper, we studied on the phoneme classification for Korean speech recognition. In the case of making large vocabulary speech recognition system, it is better to use phoneme than syllable or word as recognition unit. And, In order to study the difference of speech recognition according to the number of phoneme as recognition unit, we used the speech toolkit of OGI in U.S.A as recognition system. The result showed that the performance of diphthong being unified was better than that of seperated diphthongs, and we required the better result when we used the biphone than when using mono-phone as recognition unit.

• Korean Institute of Interior Design Journal
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• v.21 no.1
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• pp.136-147
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• 2012

This study researched about gender color preference as basic data for color application of fashion shop Facade. A HUE TONE system from V(vivid) to DK(dark) was used based on 10 colors of the IRI-120 color chart, color preference according to gender was investigated through a survey on males and females of over teenage years, and it was analyzed and presented as a color matching chart. And it was suggested as a color guideline through comprehensive analysis. Few definitions can be given through the results of this study. First, the preference degree according to gender was similar but different senses were shown visually even though the same adjective expressive vocabulary of a color image was suggested. This means there is an unchanging basic conservative disposition that males and females do not have and therefore they infer different ideas according to various environments and factors. Second, females showed more sensitive response to colors than males in the gender color preference result, which confirmed the deviation of each color group that is characteristically preferred according to a category. Third, high preferred color matches according to gender were shown for each vocabulary in various senses such as similar color matching, complementary color matching, separation color matching, and accent color matching. A universal empirical theory by general sensibility was obtained as the purpose of this study. This study suggested securement of a color design planning as basic data and the extent of usability by quantitatively showing the order of priority through the survey and analysis. Thus, the results of this study will be a great help as basic data for invigoration and commercialization of a color planning for designers and users.

• 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 Society of Computer and Information
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• v.11 no.2 s.40
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• pp.7-13
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• 2006

The advent of Semantic Web has generated several methods that can access the data on the web. Thus, it is necessary to handle the data by accessing the current web ontology as well as the existing knowledge base system. Web ontology languages are RDF(Resource Description Framework), DAML-OIL, OWL(Web Ontology Language), and so on. This paper presents the creation and the method of the ontology object model that can access, represent, and process the web ontology and the existing knowledge base. Unlike the existing access approach of web ontology using the model on memory constructed by each parser, we divide the model of web ontology into three layers such as frame-based ontology layer, generic ontology layer, and functional ontology layer. Generic ontology layer represents the common vocabulary among several domains and functional ontology layer contains the dependent vocabulary to each ontology respectively. Our model gets rid of the redundancy of the representation and enhances the reusability. Moreover, it can provide the easy representation of knowledge and the fast access of the model in the application.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3
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• pp.3-9
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• 1999

This paper presents the study on the rejection capability based on anti-phone modeling for vocabulary independent speech recognition system. The rejection system detects and rejects out-of-vocabulary words which were not included in candidate words which are defined while the speech recognizer is made. The rejection system can be classified into two categories by their implementation methods, keyword spotting method and utterance verification method. The keyword spotting method uses an extra filler model as a candidate word as well as keyword models. The utterance verification method uses the anti-models for each phoneme for the calculation of confidence score after it has constructed the anti-models for all phonemes. We implemented an utterance verification algorithm which can be used for vocabulary independent speech recognizer. We also compared three kinds of means for the calculation of confidence score, and found out that the geometric mean had shown the best result. For the normalization of confidence score, usually Sigmoid function is used. On using it, we compared the effect of the weight constant for Sigmoid function and determined the optimal value. And we compared the effects of the size of cohort set, the results showed that the larger set gave the better results. And finally we found out optimal confidence score threshold value. In case of using the threshold value, the overall recognition rate including rejection errors was about 76%. This results are going to be adapted for stock information system based on speech recognizer which is currently provided as an experimental service by Korea Telecom.

• The Journal of the Acoustical Society of Korea
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• v.14 no.5
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• pp.44-50
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• 1995

This paper describes a large-vocabulary continuous speech recognition system using continuous hidden Markov models for the Korean language. To improve the performance of the system, we study on the selection of speech modeling units, inter-word modeling, search algorithm, and grammars. We used triphones as basic speech modeling units, generalized triphones and function word-dependent phones are used to improve the trainability of speech units and to reduce errors in function words. Silence between words is optionally inserted by using a silence model and a null transition. Word pair grammar and bigram model based oil word classes are used. Also we implement a search algorithm to find N-best candidate sentences. A postprocessor reorders the N-best sentences using word triple grammar, selects the most likely sentence as the final recognition result, and finally corrects trivial errors related with postpositions. In recognition tests using a 3,000-word continuous speech database, the system attained $93.1\%$ word recognition accuracy and $73.8\%$ sentence recognition accuracy using word triple grammar in postprocessing.

• The Journal of the Acoustical Society of Korea
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• v.16 no.6
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• pp.106-109
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• 1997

For the practical isolated word recognition system, the ability to reject the out-of -vocabulary(OOV) is required. In this paper, we present a rejection method which uses the clustered phoneme modeling combined with postprocessing by likelihood ratio scoring. Our baseline speech recognition system was based on the whole-word continuous HMM. And 6 clustered phoneme models were generated using statistical method from the 45 context independent phoneme models, which were trained using the phonetically balanced speech database. The test of the rejection performance for speaker independent isolated words recogntion task on the 22 section names shows that our method is superior to the conventional postprocessing method, performing the rejection according to the likelihood difference between the first and second candidates. Furthermore, this clustered phoneme models do not require retraining for the other isolated word recognition system with different vocabulary sets.

• The Journal of the Acoustical Society of Korea
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• v.10 no.4
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• pp.5-11
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• 1991

This paper suggests a segmentation method of speech signal into phonemic units. The suggested segmentation system is speaker-independent and performed without anyprior information of speech signal. In segmentation process, we first divide input speech signal into purevoiced region and not pure voiced speech regions. After then we apply the second algorithm which segments each region into the detailed phonemic units by using the voiced detection parameters, i.e., the time variation of 0th LPC cepstrum coefficient parameter and the ZCR parameter. Types of speech, used to prove the availability of segmentation algorithm suggested in this paper, are the vocabulary composed of isolated words and continuous words. According to the experiments, the successful segmentation rate for 507 phonemic units involved in the total vocabulary is 91.7%.

• The Journal of Information Systems
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• v.27 no.2
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• pp.77-94
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• 2018

Purpose As the amount of data became enormous, it became a time when more efforts were needed to find the necessary information. Curation is a new term similarly to the museum curator, which is a service that helps people to collect, share, and value the contents of the Internet. In SNS, hash tag is used for emotional vocabulary to be transmitted between users by using (#) tag. Design/methodology/approach As the amount of data became enormous, it became a time when more efforts were needed to find the necessary information. Curation is a new term similarly to the museum curator, which is a service that helps people to collect, share, and value the contents of the Internet. In SNS, hash tag is used for emotional vocabulary to be transmitted between users by using (#) tag. Findings This study base on seven emotional sets such as 'Happy', 'Angry', 'Sad', 'Bad', 'Fearful', 'Surprised', 'Disgusted' to construct 327 emotional seeds and utilize the autofill function of web browser to collect 1.5 million emotional words from emotional seeds. The emotional dictionary of this study is considered to be meaningful as a tool to make emotional judgment from unstructured data.