Comparative Analysis of Automatic Speech Recognition Techniques
- DOI
- 10.2991/978-94-6463-136-4_79How to use a DOI?
- Keywords
- ASR; MFCC; DTW; HMM; ML
- Abstract
It’s most crucial method of transferring data is interaction. Speech is the most common way of data exchange. According to with linguistic survey, there are 179 languages and 544 dialects spoken in India. Current India has 18 scheduled dialects and several unscheduled languages. The primary goal of this paper is to give a thorough comparative evaluation of the relevant research on automated speech recognition. We observe potential prospects, problems, and methodologies, as well as locate, evaluate, and synthesize data from research in order to give empirical responses to scientific concerns. The survey was done by using appropriate research publications period between 2010 and 2021. The goal of this comprehensive examination is to synthesize the current best research on automated speech recognition by combining the findings of several investigations.
- Copyright
- © 2023 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.
Cite this article
TY - CONF AU - Suvarnsing G. Bhable AU - Ratnadeep R. Deshmukh AU - Charansing N. Kayte PY - 2023 DA - 2023/05/01 TI - Comparative Analysis of Automatic Speech Recognition Techniques BT - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022) PB - Atlantis Press SP - 897 EP - 904 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-136-4_79 DO - 10.2991/978-94-6463-136-4_79 ID - Bhable2023 ER -