In: Proceeding of the International Conference on Computer and Information Technology (ICCIT), pp. 222–226 (2010)Īhmed, M., Shill, P.C., Islam, K., Mollah, M.A.S., Akhand, M.A.H., Acoustic modeling using deep belief network for Bangla speech recognition. In: Proceeding of the International Conference on Signal and Image Processing (ICSIP), pp. IEEE (2011)Įity, Q.N., Banik, M., Lisa, N.J., Hassan, F., Hossain, M.S., Huda, M.N.: Bangla speech recognition using two stage multilayer neural networks. In: 2011 International Conference on Speech Database and Assessments (Oriental COCOSDA), pp.
ICASSP 1, 178–181 (1976)ĭas, B., Mandal, S., Mitra, P.: Bengali speech corpus for continuous automatic speech recognition system. Pramanik, M., Kido, K.: Bengali speech: formant structures of single vowels and initial vowels of words. Keywordsįorgie, J.W., Forgie, C.D.: Results obtained from a vowel recognition computer program. The system has been tested on a data set of 3710 Bangla Swarabarna (Vowel) Phonemes, and an accuracy of 99.06% has been obtained using Ensemble Learning. In this paper, a Bangla Phoneme Recognition system is proposed to help in the development of a Bangla Speech Recognizer using a new Linear Predictive Cepstral Coefficient-based feature, namely LPCC-2. Speech Recognition in Bangla is a bit complicated task mostly due to the presence of compound characters. It is these sounds which constitute the vocabulary of that language.
Every language encompasses a unique set of atomic sounds termed as Phonemes. The process of identification of words and phrases from voice signals is known as Speech Recognition.
A speech-based UI can be a solution to this, considering the fact that it is one of the most spontaneous and natural modes of interaction for most people. An array of devices have emerged lately for easing our daily life but one concern has always been towards designing simple user interface (UI) for such devices.
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