• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.11-22
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• 2022

Recently, research and development using various Artificial Intelligence (AI) technologies are being conducted in the field of education. Among the AI in Education (AIEd), conversational agents are not limited by time and space, and can learn more effectively by combining them with various AI technologies such as voice recognition and translation. This paper conducted a trend analysis on platforms that have a large number of users and used conversational agents for English learning among commercialized application. Currently commercialized educational platforms using conversational agent through trend analysis has several limitations and problems. To analyze specific problems and limitations, a comparative experiment was conducted with the latest pre-trained large-capacity dialogue model. Sensibleness and Specificity Average (SSA) human evaluation was conducted to evaluate conversational human-likeness. Based on the experiment, this paper propose the need for trained with large-capacity parameters dialogue models, educational data, and information retrieval functions for effective English conversation learning.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1191-1194
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• 1995

A conversational programming system for turning processes was studied to enhance the user friendlness of an NC by adopting man-machine interface functions through Visual C $^{++}$ programming tool under the Windows 95 environment. Shop floor programming performance was incorporated in the developed CAM module. In order to increase flexibility of the man-machine interface, graphic based programmin tool have been developed. An NC turning machine equipped whit an open architecture PCNC was used as a test bed of the system. Perfomance of the system was verified through case studies..

• The Journal of Korea Robotics Society
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• v.4 no.1
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• pp.49-55
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• 2009

The development of IT technology makes the functions and services of robots be integrated, and thus the robots become more intelligent and useful. As sophisticated usage of robots has evolved, direct communication by human language is necessary to increase the efficiency of their usage. In this paper, we propose a conversational interface platform for integrated service robots using MS Robotics Studio. The proposed platform consists of three types of components: a conversation manager to control the flows of the integrated service robots, a user interface to interact with users, and multiple service robots to perform actions or services. For a test-bed of the proposed platform, we build a schedule manager system and confirm the usability through SUS subject test by comparing the schedule manager system with MS Outlook.

• ETRI Journal
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• v.28 no.6
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• pp.807-810
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• 2006

This letter presents a prediction model for sentence-final intonations for Korean conversational-style text-to-speech systems in which we introduce the linguistic feature of 'modality' as a new parameter. Based on their function and meaning, we classify tonal forms in speech data into tone types meaningful for speech synthesis and use the result of this classification to build our prediction model using a tree structured classification algorithm. In order to show that modality is more effective for the prediction model than features such as sentence type or speech act, an experiment is performed on a test set of 970 utterances with a training set of 3,883 utterances. The results show that modality makes a higher contribution to the determination of sentence-final intonation than sentence type or speech act, and that prediction accuracy improves up to 25% when the feature of modality is introduced.

• Phonetics and Speech Sciences
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• v.2 no.1
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• pp.3-11
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• 2010

The present study confirmed the intelligibility improvement benefit of clear speech by investigating the intelligibility of Korean stops produced in different speaking styles: conversational, citation-form, and clear speech. This finding supports the Hypo- & Hyper-speech theory that speakers adjust vocal effort to accommodate hearers' speech perception difficulty. A progressive intelligibility improvement was found for the three speaking styles investigated: clear speech was more intelligible than citation-form speech citation-form speech was more intelligible than conversational speech and clear speech was also more intelligible than conversational speech. These findings suggest that the manipulations to elicit three distinct speaking styles in a laboratory setting were successful. Korean lenis stops showed the least intelligibility improvement among the three Korean stop types, and this result suggests that lenis stops should be more resistant to intelligibility enhancement efforts in clear speech than aspirated and fortis stops.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.2
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• pp.29-39
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• 1998

A conversational programming system for turning processes was studied to enhance the user friendliness of a NC Lathe by adopting man-machine interface functions through Delphi programming tool under the Windows 95 environment. Functions of tool collision checking were developed through zone limitation algorithms. Final shape of workpiece was generated by means of tree structure algorithm. Shop floor programming performance was incorporated in the developed CAM module. In order to increase flexibility of the man-machine interface, graphic based programming tools have been developed. A NC turning machine equipped with an open architecture PCNC was used as a test bed of the system. Performance of the system was verified through case studies.

• Proceedings of the KSPS conference
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• 2006.11a
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• pp.135-138
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• 2006

In this paper, we introduce a method for extracting grapheme-to-phoneme conversion rules from the transcription of speech synthesis database and a prosody modeling method using the light version of ToBI for a Korean conversational style TTS. We focused on representing the characteristics of the conversational speech style and the experimental results show that our proposed methods are suitable for developing a Korean conversional style TTS.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.83-86
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• 2003

This paper presents our style-based language model adaptation for Korean conversational speech recognition. Korean conversational speech is observed various characteristics of content and style such as filled pauses, word omission, and contraction as compared with the written text corpora. For style-based language model adaptation, we report two approaches. Our approaches focus on improving the estimation of domain-dependent n-gram models by relevance weighting out-of-domain text data, where style is represented by n-gram based tf*idf similarity. In addition to relevance weighting, we use disfluencies as predictor to the neighboring words. The best result reduces 6.5％ word error rate absolutely and shows that n-gram based relevance weighting reflects style difference greatly and disfluencies are good predictor.

• Design Convergence Study
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• v.18 no.3
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• pp.71-87
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• 2019

Previous research has shown that the use of self-disclosure, the process of revealing personal thoughts and feelings, in conversational agents (CAs) increases overall user evaluations. However, research exploring the effects of self-disclosure in different situations or dialogue types is limited. This study investigated the effects of self-disclosure and dialogue type (task- vs. social-oriented) on trust, usefulness, and usage intention. Results showed significant interaction effects between self-disclosure and dialogue type. For CAs that did not use self-disclosure, trust, usefulness, and usage intention were higher in task-oriented dialogues. In contrast, CAs that did use self-disclosure had higher trust, usefulness, and usage intention in social-oriented dialogues. These results suggest that researchers and designers should consider the specific dialogue types and corresponding user goals when adding human qualities, such as self-disclosure, to CAs.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.330-338
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• 2002

Spontaneous speech is ungrammatical as well as serious phonological variations, which make recognition extremely difficult, compared with read speech. In this paper, for conversational speech recognition, we analyze the transcriptions of the real conversational speech, and then classify the characteristics of conversational speech in the speech recognition aspect. Reflecting these features, we obtain the baseline system for conversational speech recognition. The classification consists of long duration of silence, disfluencies and phonological variations; each of them is classified with similar features. To deal with these characteristics, first, we update silence model and append a filled pause model, a garbage model; second, we append multiple phonetic transcriptions to lexicon for most frequent phonological variations. In our experiments, our baseline morpheme error rate (WER) is 31.65%; we obtain MER reductions such as 2.08% for silence and garbage model, 0.73% for filled pause model, and 0.73% for phonological variations. Finally, we obtain 27.92% MER for conversational speech recognition, which will be used as a baseline for further study.