대한전자공학회:학술대회논문집 (Proceedings of the IEEK Conference)
- 대한전자공학회 1999년도 추계종합학술대회 논문집
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- Pages.672-675
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- 1999
한국어 음절 인식을 위한 MLP 신경망 구조 및 특징 추출에 관한 연구
A Study on MLP Neural Network Architecture and Feature Extraction for Korean Syllable Recognition
초록
In this paper, we propose a MLP neural network architecture and feature extraction for Korean syllable recognition. In the proposed syllable recognition system, firstly onset is classified by onset classification neural network. And the results information of onset classification neural network are used for feature selection of imput patterns vector. The feature extraction of Korean syllables is based on sonority. Using the threshold rate separate the syllable. The results of separation are used for feature of onset. nucleus and coda. ETRI's SAMDORI has been used by speech DB. The recognition rate is 96% in the speaker dependent and 93.3% in the speaker independent.
키워드