• Darshita R. Shah
• Prof. Swarndeep Saket

Speech processing one of the new areas for research with ANN(Artificial Neural Network) system in current generation. Although emotion detection from speech is a relatively new field of research, and has many potential applications. In human-computer or human-human interaction systems, emotion recognition systems could provide users with improved services by being adaptive to their emotions. Recent works on effect detection using speech and different issues related to affect detection has been presented. The primary challenges of emotion recognition are choosing the emotion recognition corpora (speech database),identification of different features related to speech and an appropriate choice of a classification model. Different types of methods to collect emotional speech data and issues related to them are covered by this presentation along with the previous works review. Here is use Mel Frequency Cepstral Coefficient (MFCC) with pre - emphasis technique for identify feature and then applied machine learning for classifying types of emotions from speech frame with high accuracy.

Speech Emotion Recognition; MFCC(Mel Frequency Cepstral Coefficient); Support Vector Mechanism (SVM).

"Analysis on Speech processing technique using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.107-115, December-2018, Available :http://www.jetir.org/papers/JETIR1812317.pdf

"Analysis on Speech processing technique using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp107-115, December-2018, Available at : http://www.jetir.org/papers/JETIR1812317.pdf