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Application of end-to-end speech recognition in Chinese chess software

Published: 30 May 2024 Publication History

Abstract

This paper proposes the integration of end-to-end speech recognition technology into Chinese chess software. We collected and presented a dataset of Chinese chess terminology instructions, and extracting the Mel Frequency Cepstral Coefficients (MFCC) from the speech signals to serve as features. Additionally, we employed the Wenet platform to establish an end-to-end speech recognition model and developed a Chinese chess software system for speech recognition and control. Through experimental we demonstrated this system has the capability to achieve accurate speech recognition and control for playing Chinese chess.

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    ICIEAI '23: Proceedings of the 2023 International Conference on Information Education and Artificial Intelligence
    December 2023
    1132 pages
    ISBN:9798400716157
    DOI:10.1145/3660043
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 30 May 2024

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