ETRI-Knowledge Sharing Plaform

KOREAN
논문 검색
Type SCI
Year ~ Keyword

Detail

Conference Paper End-to-end Korean Digits Speech Recognition
Cited 1 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Jong-hyuk Roh, Kwantae Cho, Youngsam Kim, Sangrae Cho
Issue Date
2019-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.1137-1139
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC46691.2019.8939697
Abstract
The traditional speech recognition model consisting of an acoustic model and a language model is mainly used. Recently, an end-to-end speech recognition model consisting of a single integrated neural network model is being studied. This model has the advantage that it does not require a lot of training and it is easy to understand the structure of the model. In this paper, we designed the end-to-end model for Korean digit speech recognition and showed the performance results. We tried the digit speech recognition model in two forms: Word model and character model.
KSP Keywords
End to End(E2E), End-to-End Speech Recognition, Integrated neural network, Language model, Recognition model, acoustic model, neural network model