• The Journal of the Acoustical Society of Korea
• /
• v.15 no.4
• /
• pp.24-31
• /
• 1996

In this paper, we present a speech translation system for hotel reservation, KT_STS(Korea Telecom Speech Translation System). KT-STS is a speech-to-speech translation system which translates a spoken utterance in Korean into one in Japanese. The system has been designed around the task of hotel reservation(dialogues between a Korean customer and a hotel reservation de나 in Japan). It consists of a Korean speech recognition system, a Korean-to-Japanese machine translation system and a korean speech synthesis system. The Korean speech recognition system is an HMM(Hidden Markov model)-based speaker-independent, continuous speech recognizer which can recognize about 300 word vocabularies. Bigram language model is used as a forward language model and dependency grammar is used for a backward language model. For machine translation, we use dependency grammar and direct transfer method. And Korean speech synthesizer uses the demiphones as a synthesis unit and the method of periodic waveform analysis and reallocation. KT-STS runs in nearly real time on the SPARC20 workstation with one TMS320C30 DSP board. We have achieved the word recognition rate of 94. 68% and the sentence recognition rate of 82.42% after the speech recognition tests. On Korean-to-Japanese translation tests, we achieved translation success rate of 100%. We had an international joint experiment in which our system was connected with another system developed by KDD in Japan using the leased line.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.7
• /
• pp.231-243
• /
• 2024

As generative artificial intelligence (AI) services become more diversified and widely used, attempts and discussions on their application in education have become active. The purpose of this study is to investigate and analyze general and work-related perceptions, utilization, and needs regarding generative AI in elementary and secondary education. A survey was conducted among teachers and staff in Chungcheongbuk-do, and 934 responses were analyzed. The main research results are as follows: First, their work-related use of generative AI was lower than their general use, and considering the periodic frequency of more than once a month, the rate was much lower. Second, the main expectation when using generative AI in work appears to be improved work efficiency. Third, regarding the use of generative AI for each task, differences in perception of its usefulness were noticeable depending on position and occupation. They generally responded positively to the usefulness of generative AI in processing documents. To facilitate the use of generative AI for work by elementary and secondary teachers and staff, it is necessary to create an environment that promotes its use while ensuring safety against potential side effects. Additionally, requirements and needs should be considered depending on the position and occupation.