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Conference Paper
End-to-end Korean Digits Speech Recognition
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- 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
- 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, Neural network model, Recognition model, acoustic model, neural network(NN)