This study aims to explore the characteristics of cloud-based speech recognition system’s application of phonological rules and to present the criteria for selecting a high-performance cloud-based Open API for developing an applied speech recognition system. Therefore, assessing the recognition rate of speech recognition systems for phonological rules will help to understand the characteristics of speech recognition systems. In the speech recognition process, meaningful sentences should be made in terms of syllables by finding the exact morphemes. The speech recognition system should accurately recognize phonological changes regardless of whether a pronouncing dictionary exists. The process of creating words either uses pronouncing dictionaries according to the characteristics of the speech recognition system, using information through deep learning of vocal information without pronouncing dictionaries. The recognition unit makes a word for the extracted speech information of the speech. Speech recognition systems are largely divided into pre-processing and recognition units. The improved performance and ease of development of speech recognition systems are being applied in a variety of areas. Cloud-based speech recognition Open API has saved a lot of time, effort, and money to develop an applied speech recognition system. By collecting large amount of speech data for development of speech recognition system, high performance computer for learning large volume speech data is not needed. The cloud-based speech recognition engine addresses the difficulties of developing speech recognition systems. Speech recognition systems have significantly improved performance with cloud computing technology and application of artificial intelligence. #AZURE SPEECH TO TEXT OUTPUT LEXICAL LICENSE#Open Access This is an open access article distributed under the CC BY-NC 4.0 license ( ). 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. 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. The performance of speech recognition of Korean phonological rules was good for /l/nasalization and /h/deletion. By phonological rule, Kakao showed good performance in all areas except for nasalization and Flat stop sound formation in final syllable. As a result of the experiment, Kakao and MS showed good performance in speech recognition. 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.
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