Emotion transformation from neutral to 3 emotions of speech signal using DWT and adaptive filtering techniques

Voice transformation is an application in speech processing which involves modification of speech signal of source speaker to a target speaker. This paper explains transformation of Neutral speech of target speaker into Angry, Happy and Sad emotions. In this algorithm modeling of speech is performed using Discrete Wavelet Transform (DWT) for the emotions of Source and Target speakers. Linear least square method is used to find the best-fit n^th order polynomial for the given set of data points to build a transformation function. Finally the transformed signal is generated using Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) adaptive filtering techniques and the results of the 3 adaptive filters is compared. The results are evaluated by Subjective evaluation by carrying out a formal listening test. Objective evaluation is performed by calculating the parameters of transformed speech using Mean Square Error (MSE), Euclidean Distance (ED) and Correlation Coefficient (CC).