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Nepali Speech Recognition using RNN-CTC Model

by Paribesh Regmi, Arjun Dahal, Basanta Joshi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 31
Year of Publication: 2019
Authors: Paribesh Regmi, Arjun Dahal, Basanta Joshi
10.5120/ijca2019918401

Paribesh Regmi, Arjun Dahal, Basanta Joshi . Nepali Speech Recognition using RNN-CTC Model. International Journal of Computer Applications. 178, 31 ( Jul 2019), 1-6. DOI=10.5120/ijca2019918401

@article{ 10.5120/ijca2019918401,
author = { Paribesh Regmi, Arjun Dahal, Basanta Joshi },
title = { Nepali Speech Recognition using RNN-CTC Model },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2019 },
volume = { 178 },
number = { 31 },
month = { Jul },
year = { 2019 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number31/30732-2019918401/ },
doi = { 10.5120/ijca2019918401 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:51:54.188862+05:30
%A Paribesh Regmi
%A Arjun Dahal
%A Basanta Joshi
%T Nepali Speech Recognition using RNN-CTC Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 31
%P 1-6
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a Neural Network based Nepali Speech Recognition model. RNN (Recurrent Neural Networks) is used for processing sequential audio data. CTC (Connectionist Temporal Classification) [1] technique is applied allowing RNN to train over audio data. CTC is a probabilistic approach of maximizing the occurrence probability of the desired labels from RNN output. After processing through RNN and CTC layers, Nepali text is obtained as output. This paper also defines a character set of 67 Nepali characters required for transcription of Nepali speech to text.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Intelligence Machine Learning Automatic Speech Recognition Recurrent Neural Network Connectionist Temporal Classification Softmax Hidden Markov Model Nepali Speech Recognition Long-Short Term Memory (LSTM) Backpropagation Character Error Rate

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