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.