An investigation and analysis on automatic speech recognition systems

Title

An investigation and analysis on automatic speech recognition systems

Creator

Siva Balan R.V.; Vignesh K.; Jose T.; Kalpana P.; Jothikumar R.

Description

A crucial part of a Speech Recognition System (SRS) is working on its most fundamental modules with the latest technology. While the fundamentals provide basic insights into the system, the recent technologies used on it would provide more ways of exploring and exploiting the fundamentals to upgrade the system itself. These upgrades end up in finding more specific ways to enhance the scope of SRS. Algorithms like the Hidden Markov Model (HMM), Artificial Neural Network (ANN), the hybrid versions of HMM and ANN, Recurrent Neural Networks (RNN), and many similar are used in accomplishing high performance in SRS systems. Considering the domain of application of SRS, the algorithm selection criteria play a critical role in enhancing the performance of SRS. The algorithm chosen for SRS should finally work in hand with the language model conformed to the natural language constraints. Each language model follows a variety of methods according to the application domain. Hybrid constraints are considered in the case of geography-specific dialects. 2024 by author(s).

Source

Journal of Autonomous Intelligence, Vol-7, No. 3

Date

2024-01-01

Publisher

Frontier Scientific Publishing

Subject

ensemble methods; language model; natural language; speech processing; speech recognition system; speech technology

Coverage

Siva Balan R.V., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Vignesh K., Department of Management Studies, Kumaraguru College of Technology, Coimbatore, 641049, India; Jose T., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Kalpana P., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Jothikumar R., Department of Computer Science and Engineering, Shadan College of Engineering and Technology, Hyderabad, 500086, India

Rights

All Open Access; Gold Open Access

Relation

ISSN: 26305046

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.32629/jai.v7i3.1060

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