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Journal Article KsponSpeech: Korean Spontaneous Speech Corpus for Automatic Speech Recognition
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Authors
Jeong-Uk Bang, Seung Yun, Seung-Hi Kim, Mu-Yeol Choi, Min-Kyu Lee, Yeo-Jeong Kim, Dong-Hyun Kim, Jun Park, Young-Jik Lee, Sang-Hun Kim
Issue Date
2020-10
Citation
Applied Sciences, v.10, no.19, pp.1-17
ISSN
2076-3417
Publisher
MDPI
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.3390/app10196936
Abstract
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.
KSP Keywords
Clean environment, End to End(E2E), End-to-End Speech Recognition, Open Data, Recognition model, Speech corpus, automatic speech recognition(ASR), large-scale, open-domain dialog, spontaneous speech
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
CC BY