Phoneme-to-Grapheme Conversion Based Large-Scale Pre-Training for End-to-End Automatic Speech Recognition

Author(s):  
Ryo Masumura ◽  
Naoki Makishima ◽  
Mana Ihori ◽  
Akihiko Takashima ◽  
Tomohiro Tanaka ◽  
...  
2020 ◽  
Vol 10 (19) ◽  
pp. 6936 ◽  
Author(s):  
Jeong-Uk Bang ◽  
Seung Yun ◽  
Seung-Hi Kim ◽  
Mu-Yeol Choi ◽  
Min-Kyu Lee ◽  
...  

This paper introduces a large-scale spontaneous speech corpus of Korean, named KsponSpeech. This corpus contains 969 h of general open-domain dialog utterances, spoken by about 2000 native Korean speakers in a clean environment. All data were constructed by recording the dialogue of two people freely conversing on a variety of topics and manually transcribing the utterances. The transcription provides a dual transcription consisting of orthography and pronunciation, and disfluency tags for spontaneity of speech, such as filler words, repeated words, and word fragments. This paper also presents the baseline performance of an end-to-end speech recognition model trained with KsponSpeech. In addition, we investigated the performance of standard end-to-end architectures and the number of sub-word units suitable for Korean. We investigated issues that should be considered in spontaneous speech recognition in Korean. KsponSpeech is publicly available on an open data hub site of the Korea government.


2019 ◽  
Vol 15 (7) ◽  
pp. P162-P163
Author(s):  
Francesca K. Cormack ◽  
Nick Taptiklis ◽  
Jennifer H. Barnett ◽  
Merina Su

Author(s):  
Qi Liu ◽  
Zhehuai Chen ◽  
Hao Li ◽  
Mingkun Huang ◽  
Yizhou Lu ◽  
...  

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