<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Speech recognition is an interdisciplinary subfield of natural language processing (NLP) that facilitates the recognition and translation of spoken language into text by machine. Speech recognition plays an important role in digital transformation. It is widely used in different areas such as education, industry, and healthcare and has recently been used in many Internet of Things and Machine Learning applications. The process of speech recognition is one of the most difficult processes in computer science. Despite numerous searches in this domain, an optimal method for speech recognition has not yet been found. This is due to the fact that there are many attributes that characterize natural languages and every language has its particular highlights. The aim of this research is to provide a comprehensive understanding of the various techniques within the domain of Speech Recognition through a systematic literature review of the existing work. We will introduce the most significant and relevant techniques that may provide some directions in the future research.</p></abstract>

Speech recognition is an interdisciplinary subfield of natural language processing (NLP) that facilitates the recognition and translation of spoken language into text by machine. Speech recognition plays an important role in digital transformation. It is widely used in different areas such as education, industry, and healthcare and has recently been used in many Internet of Things and Machine Learning applications. The process of speech recognition is one of the most difficult processes in computer science. Despite numerous searches in this domain, an optimal method for speech recognition has not yet been found. This is due to the fact that there are many attributes that characterize natural languages and every language has its particular highlights. The aim of this research is to provide a comprehensive understanding of the various techniques within the domain of Speech Recognition through a systematic literature review of the existing work. We will introduce the most significant and relevant techniques that may provide some directions in the future research.

Automatic Speech Recognition: A Comprehensive Survey

Faculty of Contemporary Sciences and Technologies

SEEU Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Automatic Speech Recognition: A Comprehensive Survey"}

Speech recognition is an interdisciplinary subfield of natural language processing (NLP) that facilitates the recognition and translation of spoken language...

Automatic Speech Recognition: A Comprehensive Survey

Online veröffentlicht: 06. Apr. 2021

Seitenbereich: 86 - 112

DOI: https://doi.org/10.2478/seeur-2020-0019

Schlüsselwörter
Automatic Speech Recognition (ASR), End-to-End Systems, Hybrid Systems, Low Resource Language

© 2020 Amarildo Rista et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Automatic Speech Recognition: A Comprehensive Survey

Online veröffentlicht: 06. Apr. 2021

Seitenbereich: 86 - 112

DOI: https://doi.org/10.2478/seeur-2020-0019

SchlüsselwörterAutomatic Speech Recognition (ASR), End-to-End Systems, Hybrid Systems, Low Resource Language

© 2020 Amarildo Rista et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Automatic Speech Recognition (ASR), End-to-End Systems, Hybrid Systems, Low Resource Language