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Korean speech recognition based on grapheme문자소 기반의 한국어 음성인식
- Other Titles
- 문자소 기반의 한국어 음성인식
- Authors
- Lee, Mun-hak; Chang, Joon Hyuk
- Issue Date
- Sep-2019
- Publisher
- ACOUSTICAL SOC KOREA
- Keywords
- Automatic speech recognition; Deep learning; Lexicon; Kaldi
- Citation
- JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA, v.38, no.5, pp.601 - 606
- Indexed
- SCOPUS
KCI
- Journal Title
- JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA
- Volume
- 38
- Number
- 5
- Start Page
- 601
- End Page
- 606
- ISSN
- 1225-4428
- Abstract
- This paper is a study on speech recognition in the Korean using grapheme unit (Cho-sumg [onset], Jung-sung [nucleus], Jong-sung [coda]). Here we make ASR (Automatic speech recognition) system without G2P (Grapheme to Phoneme) process and show that Deep learning based ASR systems can learn Korean pronunciation rules without G2P process. The proposed model is shown to reduce the word error rate in the presence of sufficient training data.
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Related Researcher
- Chang, Joon-Hyuk
- COLLEGE OF ENGINEERING (SCHOOL OF ELECTRONIC ENGINEERING)