MFCC Using Speech Recognition in Computer Applications for Deaf
S. Elavarasi1, G. Suseendran2
1S. Elavarasi, Ph.D, Research Scholar, Department of Computer Science, Vels Institute of Science, Technology and Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
2Dr. G. Suseendran, Assistant Professor, Department of Information Technology, Vels Institute of Science, Technology and Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
Manuscript received on 10 October 2019 | Revised Manuscript received on 19 October 2019 | Manuscript Published on 02 November 2019 | PP: 217-224 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B10360982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1036.0982S1119
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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 has lately evolved as a beneficial computer technology involving various interactive speech based applications in this domain. For communicating with one another, speech forms the basic foundation. Utilizing this way of communication in the technology domain, the technique of speech recognition is formulated. This technique considers the input speech in order to extract significant information thereby drawing accurate decision related to the concerned text. Here the research proposes a technique by effectively incorporating speech recognition approach for handling web portal via voice (be it from any place or time) for accessing data. Advent and growth in technology has led to formation of STT (speech–to–text) conversion model which generates a text format of the speech that’s beneficial for the Deaf individuals and in other realms too. Data mining has achieved great success in examining the acoustic features related to sound and speech. The existing research employs the MFCC (Mel Frequency Cepstrum Coefficients) for extracting acoustic features of a voice that is identifying the gender of a given voice. Following are the stages in the system proposed: 1. speech pre-processing, 2. feature extraction, 3. converting to text4. Classification5. Displaying the web portal and 6. Storing the web portal. The research depicts speech recognition and analysis as a speech process. The STT (speech to text) model includes two levels, first being the document level and second is the sentence level. The proposed system is beneficial for the deaf individuals for accessing the data be it from any place or time and in other realms too. The system yields in great accuracy in the given time span.
Keywords: Speech Recognition, Speech–to–text (STT), Mel Frequency Cepstrum Coefficients (MFCC), Feature Extraction, Preprocessing, Classification.
Scope of the Article: Computer Science and Its Applications