MFCC using Speech Recognition in Computer Applications for Deaf

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 preprocessing, 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.