Detection of attributes for Bengali phoneme in continuous speech using deep neural network

Author

Bhowmik, Tanmay ; Mukherjee, Sankar ; Das Mandal, Shyamal Kumar

Author_Institution

Centre for Educ. Technol., IIT Kharagpur, Kharagpur, India

fYear

2015

fDate

19-20 Feb. 2015

Firstpage

103

Lastpage

108

Abstract

Hidden Markov Model (HMM) has contributed greatly in the area of speech recognition during last two decades. However, in recent days, detection-based, bottom-up speech recognition techniques achieve high success rate. In this detection-based, bottom-up approach of speech recognition, first step is detection of speech attributes like place and manner of articulation of the phonemes. This paper describes about the detection of attributes which leads to identification of place and manner of articulation of Bengali phonemes using Deep Neural Network (DNN).

Keywords

hidden Markov models; natural language processing; neural nets; speech recognition; Bengali phoneme; DNN; HMM; continuous speech; deep neural network; detection-based bottom-up speech recognition techniques; hidden Markov model; speech attribute detection; Accuracy; Dentistry; Detectors; Hidden Markov models; Speech; Speech recognition; Training; deep belief network; deep neural network; manner of articulation; place of articulation; speech attribute;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Integrated Networks (SPIN), 2015 2nd International Conference on

Conference_Location

Noida

Print_ISBN

978-1-4799-5990-7

Type

conf

DOI

10.1109/SPIN.2015.7095329

Filename

7095329