Isolated telugu speech recognition on T-DSCC and DNN techniques

Abstract

Communication is the major path to convey the information. Speech is the best mode for conveying the information. Human to human information can be exchanged through some particular language. But the interaction between human and machine is the major challenge which deals with ASR (Automatic speech recognition). This research recognizes speaker independent data which gives good results by using T-DSCC (Teager energy operator delta spectral cepstral coefficients) feature extraction technique and DNN (Deep Neural Networks) feature classification technique. This paper also uses CASA technique for pre-processing the speech signals. This research is done by creating the database for 10 most speak able isolated words in Telugu.