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19 October 2022 Construction of modern Chinese standard for computer language disfluency detection
Jiantao Li, Yunqiu Zhang, Jianshe Zhou, Jie Liu
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Proceedings Volume 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering; 1229462 (2022) https://doi.org/10.1117/12.2639916
Event: 7th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2022), 2022, Xishuangbanna, China
Abstract
Spoken text disfluency detection is an important component of speech computer recognition systems, and its goal is to effectively identify and remove spoken phenomena such as repetition, pauses, corrections and redundancy contained in AI speech recognition text data, thereby making spoken text data more concise and increasing the readability of its text data, and the technology helps to improve the correctness of computer language information processing tasks. However, in computer science or in linguistics, research on computer language disfluency detection techniques for modern Chinese word classes is almost in an academic gap. Based on a qualitative and quantitative analysis of 50,000 items of Chinese conference corpus, this study defines what is non-sentence elements in modern Chinesen and using the spoken language corpus, established a reference model for computer processing of disfluency detection components.
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Jiantao Li, Yunqiu Zhang, Jianshe Zhou, and Jie Liu "Construction of modern Chinese standard for computer language disfluency detection", Proc. SPIE 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, 1229462 (19 October 2022); https://doi.org/10.1117/12.2639916
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KEYWORDS
Artificial intelligence
Data processing
Classification systems
Particles
Speech recognition
Data modeling
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