Speakar-Independent Isolated Word Recognition using HTK for Varhadi – a Dialect of Marathi
Sunil B. Patil1, Nita V. Patil2, Ajay S. Patil3

1Sunil B. Patil*, Research scholar, Department of Computer Science, KBCNMU, Jalgaon, India.
2Nita V. Patil, Assistant Professor, Department of Computer Science, KBCNMU, Jalgaon, India.
3Ajay S. Patil, Professor, Department of Computer Science, KBCNMU, Jalgaon, India.

Manuscript received on February 01, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 748-751 | Volume-9 Issue-3, February, 2020. | Retrieval Number:  B3832129219/2020©BEIESP | DOI: 10.35940/ijeat.B3832.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Speech recognition is widely used in the computer science to make well-organized communication between humans and computers. This paper addresses the problem of speech recognition for Varhadi, the regional language of the state of Maharashtra in India. Varhadi is widely spoken in Maharashtra state especially in Vidharbh region. Viterbi algorithm is used to recognize unknown words using Hidden Markov Model (HMM). The dataset is developed to train the system consists of 83 isolated Varhadi words. A Mel frequency cepstral coefficient (MFCCs) is used as feature extraction to perform the acoustical analysis of speech signal. Word model is implemented in speaker independent mode for the proposed varhadi automatic speech recognition system (V-ASR). The training and test dataset consist of isolated words uttered by 8 native speakers of Varhadi language. The V-ASR system has recognized the Varhadi words satisfactorily with 92.77%. recognition performance.
Keywords: Speech Recognition (SP), Varhadi, HMM, HTK, Isolated Words, Mel Frequency Cepstral Coefficient (MFCCs), PLP, Speaker Independent, Interactive Voice Response (IVR)