The Performance Evaluation of Continuous Speech Recognition Based on Korean Phonological Rules of Cloud-Based Speech Recognition Open API

Autor: Hyun Jae Yoo, Sungwoong Seo, Sun Woo Im, Gwang Yong Gim
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: International Journal of Networked and Distributed Computing (IJNDC), Vol 9, Iss 1 (2021)
Druh dokumentu: article
ISSN: 2211-7946
DOI: 10.2991/ijndc.k.201218.005
Popis: This study compared and analyzed the speech recognition performance of Korean phonological rules for cloud-based Open APIs, and analyzed the speech recognition characteristics of Korean phonological rules. As a result of the experiment, Kakao and MS showed good performance in speech recognition. By phonological rule, Kakao showed good performance in all areas except for nasalization and Flat stop sound formation in final syllable. The performance of speech recognition of Korean phonological rules was good for /l/nasalization and /h/deletion. The speech recognition performance of phonological rule words accounted for a very high percentage of the whole words speech recognition performance, and the speech recognition performance of phonological rule was more different among companies than between speakers. This study hopes to contribute to the improvement of speech recognition system performance of cloud companies for Korean phonological rules and is expected to help speech recognition developers select Open API for application speech recognition system development.
Databáze: Directory of Open Access Journals
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