Speech Recognition Using Machine Learning

DOI

10.2991/978-94-6463-738-0_33How to use a DOI?

Keywords

ASR; Speech Recognition; Signal processing; Machine Learning; Neural Networking

Abstract

The research paper focuses on studying in-depth procedures that machine learning techniques combine with deep learning and Natural Language Processing (NLP) methods to develop speech recognition models. The remarkable progress made with speech recognition technology caused it to become an important element for virtual assistants and transcription services in addition to accessibility tools. This research evaluates several speech recognition models by assessing their operational methods and technical features and their efficiency performance. Model comparison during this research study presented diverse strengths and limitations of different language training approaches. Recognition enhancement relies on both extensive data collection along with optimization of model features and extraction methods and optimization techniques. The solution provides approaches to process varied accents and contains two sets of functions that reduce background noise and achieve real-time performance. The research assesses the performance capacity of HMMs and DNNs and Transformer architectures in multilingual speech processing applications.

The research conducts studies to enhance advanced speech recognition model development by analyzing the performance characteristics of different methods. Research data obtained by experts enables both the developer community and researcher community to develop improved speech recognition systems that work across diverse acoustic environments and linguistic settings.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Gautam Kumar
AU  - Jai Kumar Vanjare
AU  - Akriti Barthwal
AU  - Yogesh Rajput
AU  - Kashish
PY  - 2025
DA  - 2025/06/22
TI  - Speech Recognition Using Machine Learning
BT  - Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
PB  - Atlantis Press
SP  - 409
EP  - 421
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-738-0_33
DO  - 10.2991/978-94-6463-738-0_33
ID  - Kumar2025
ER  -