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Detail
Journal Article
Spoken‐to‐written text conversion for enhancement of Korean–English readability and machine translation
- Authors
- HyunJung Choi, Muyeol Choi, Seonhui Kim, Yohan Lim, Minkyu Lee, Seung Yun, Donghyun Kim, Sang Hun Kim
- Issue Date
- 2024-02
- Citation
- ETRI Journal, v.46, no.1, pp.127-136
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원
- Language
- English
- Type
- Journal Article
- Abstract
- The Korean language has written (formal) and spoken (phonetic) forms that differ in their application, which can lead to confusion, especially when dealing with numbers and embedded Western words and phrases. This fact makes it difficult to automate Korean speech recognition models due to the need for a complete transcription training dataset. Because such datasets are frequently constructed using broadcast audio and their accompanying transcriptions, they do not follow a discrete rule‐based matching pattern. Furthermore, these mismatches are exacerbated over time due to changing tacit policies. To mitigate this problem, we introduce a data‐driven Korean spoken‐to‐written transcription conversion technique that enhances the automatic conversion of numbers and Western phrases to improve automatic translation model performance.
- KSP Keywords
- And phrases, Automatic conversion, Automatic translation, Korean language, Korean speech, Machine Translation(MT), Matching pattern, Model performance, Over time, Recognition model, Translation Model
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
