Investigation of Advancements in Machine Learning Algorithms for Accented Speech Recognition

Yuhao Guo

2024

Abstract

The rapid advancement in technology has catalyzed the development of machine learning models, significantly impacting various domains, including speech recognition systems. This paper delves into the historical progression and transformation of machine learning models, emphasising on the application of machine learning algorithms within the domain of Voice Activity Detection (VAD) speech recognition systems. The narrative transitions from a broad overview of machine learning frameworks to a focused discussion on speech recognition technologies, specifically addressing the challenge of accentual language recognition. Through the lens of Mel-Frequency Cepstral Coefficients (MFCC) application, the paper dissects the learning models and elucidates the segmentation and recognition processes integral to speech recognition systems. Various algorithms are briefly reviewed to underscore the ongoing enhancements and the scholarly contributions towards refining these models. However, the paper also acknowledges the inherent limitations in the current understanding and application of these models. It points out the superficial treatment of certain mainstream machine learning models and their algorithms, alongside the potential obsolescence due to rapid technological evolution. The exposition concludes by recognizing the potential gaps in the depth of understanding specific to VAD and MFCC processes, attributed to the author's academic limitations, which may impinge on the thoroughness of algorithmic familiarity.

Paper Citation

in Harvard Style

Guo Y. (2024). Investigation of Advancements in Machine Learning Algorithms for Accented Speech Recognition. In Proceedings of the 1st International Conference on Data Science and Engineering - Volume 1: ICDSE; ISBN 978-989-758-690-3, SciTePress, pages 201-205. DOI: 10.5220/0012866900004547

in Bibtex Style

@conference{icdse24,
author={Yuhao Guo},
title={Investigation of Advancements in Machine Learning Algorithms for Accented Speech Recognition},
booktitle={Proceedings of the 1st International Conference on Data Science and Engineering - Volume 1: ICDSE},
year={2024},
pages={201-205},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012866900004547},
isbn={978-989-758-690-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Science and Engineering - Volume 1: ICDSE
TI - Investigation of Advancements in Machine Learning Algorithms for Accented Speech Recognition
SN - 978-989-758-690-3
AU - Guo Y.
PY - 2024
SP - 201
EP - 205
DO - 10.5220/0012866900004547
PB - SciTePress