Speech Recognition Model for Assamese Language Using Deep Neural Network

Moirangthem Tiken Singh, Partha Pratim Barman, R. Gogoi
{"title":"Speech Recognition Model for Assamese Language Using Deep Neural Network","authors":"Moirangthem Tiken Singh, Partha Pratim Barman, R. Gogoi","doi":"10.1109/ICRIEECE44171.2018.9008668","DOIUrl":null,"url":null,"abstract":"The work presents a speech recognition model for the Assamese language of the state of Assam of India. We experimented the model on the digits of Assamese language. The Deep Neural Network is used to make the recognition model. The Long Short-Term Memory Network (LSTM), which is a special kind of Recurrent Neural Network composed of Long Short-Term Memory blocks is the primary layer of our neural network model. We also use Mel Frequency Cepstral Coefficients for choosing the speech features. Finally, the accuracy of the model is evaluated based on the recognition rate.","PeriodicalId":393891,"journal":{"name":"2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRIEECE44171.2018.9008668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The work presents a speech recognition model for the Assamese language of the state of Assam of India. We experimented the model on the digits of Assamese language. The Deep Neural Network is used to make the recognition model. The Long Short-Term Memory Network (LSTM), which is a special kind of Recurrent Neural Network composed of Long Short-Term Memory blocks is the primary layer of our neural network model. We also use Mel Frequency Cepstral Coefficients for choosing the speech features. Finally, the accuracy of the model is evaluated based on the recognition rate.
基于深度神经网络的阿萨姆语语音识别模型
这项工作提出了印度阿萨姆邦阿萨姆语的语音识别模型。我们在阿萨姆语的数字上实验了这个模型。利用深度神经网络建立识别模型。长短期记忆网络(LSTM)是神经网络模型的基础层,是由长短期记忆块组成的一种特殊的递归神经网络。我们还使用Mel频率倒谱系数来选择语音特征。最后,根据识别率对模型的准确率进行评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信