Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)

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HiTEK Multilingual Speech Identification Using Combinatorial Model

Authors
Naveenkumar T. Rudrappa1, *, Mallamma V. Reddy1
1Department of Computer Science, Rani Channamma University, Vidyasangama, Belagavi, India
*Corresponding author. Email: trnphd2019@gmail.com
Corresponding Author
Naveenkumar T. Rudrappa
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-196-8_23How to use a DOI?
Keywords
Phoneme; Phone; Syllable; Speech processing; Articulatory Phonetic
Abstract

Speech is a common form of communication as it expresses the feelings, thoughts, and intentions between human beings either verbally or non-verbally. Our research focuses on verbal communication as India is a language diverse country with more than 19500 spoken languages, considered as mother tongue. The diversity in spoken language understanding leads to Speech Processing. Speech retrieval and translation is a subfield of speech processing by which spoken sentences are recorded, stored and retrieved to identify the languages which is a major challenge in natural language processing. This paper presents MFCC-GNN combinatorial model that includes speech segmentation, morphological analyzer and generator, part of speech tagger for language identification. Multilingual speech dictionary is created and consists of 250 spoken sentences for each language. There are ten most spoken languages in India namely Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia, Urdu, Tamil and Telugu. This research considers the identification of multilingual speech particularly for Hindi, Telugu, English and Kannada. Once the language being spoken is identified the future scope is the analysis of Morphological structure for each language and then translation. Translation is conversion of the meaning of a source language speech to a target language speech.

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.

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Volume Title
Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
Series
Advances in Intelligent Systems Research
Publication Date
10 August 2023
ISBN
978-94-6463-196-8
ISSN
1951-6851
DOI
10.2991/978-94-6463-196-8_23How to use a DOI?
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

risenwbib
TY  - CONF
AU  - Naveenkumar T. Rudrappa
AU  - Mallamma V. Reddy
PY  - 2023
DA  - 2023/08/10
TI  - HiTEK Multilingual Speech Identification Using Combinatorial Model
BT  - Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
PB  - Atlantis Press
SP  - 286
EP  - 303
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-196-8_23
DO  - 10.2991/978-94-6463-196-8_23
ID  - Rudrappa2023
ER  -