论文信息 - Recognition of fear from speech using adaptive algorithm with MLP classifier

Recognition of fear from speech using adaptive algorithm with MLP classifier

Clarity and intelligibility in speech signal demands removal of noise and interference associated with the signal at the source. This poses further challenge when the speech signal is colored with human emotions. In this work, the authors have taken a novel step to enhance the emotional speech signal adaptively before classification. Most popular adaptive algorithm such as Least mean square (LMS), Normalized least mean squares (NLMS) and Recursive least square (RLS) has been put to test to obtain enhanced speech emotions. Neural network based Multilayer perceptron (MLP) classifier is used to recognize fear speech emotion as against neutral voices using effective Linear Prediction coefficients (LPCs). The accuracy has improved to approximately 77% with enhanced signal. The increased accuracy of this signal has been witnessed with RLS algorithm as against the noisy signal with corresponding algorithm.

Mihir Narayan Mohanty | Rashmirekha Ram | Hemanta Kumar Palo

[1] Jyoti Dhiman,et al. Comparison between Adaptive filter Algorithms (LMS, NLMS and RLS) , 2013 .

[2] Nikola Kasabov,et al. Adaptive Filtering with Averaging in Noise Cancellation for Voice and Speech Recognition , 2000 .

[3] Mihir Narayan Mohanty,et al. Emotion recognition using MLP and GMM for Oriya language , 2017, Int. J. Comput. Vis. Robotics.

[5] D. Signorini,et al. Neural networks , 1995, The Lancet.

[6] Mihir Narayan Mohanty,et al. Classification of Emotional Speech of Children Using Probabilistic Neural Network , 2015 .

[7] Meng Sun,et al. Speech Enhancement Under Low SNR Conditions Via Noise Estimation Using Sparse and Low-Rank NMF with Kullback–Leibler Divergence , 2015, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[8] A. Mousa,et al. Speech Signal Enhancement Using Adaptive Noise Cancellation Techniques , 2012 .

[9] Mohamed Djendi,et al. Two-channel variable-step-size forward-and-backward adaptive algorithms for acoustic noise reduction and speech enhancement , 2015, Signal Process..

[10] S. Haykin,et al. Adaptive Filter Theory , 1986 .

[11] Mihir Narayan Mohanty,et al. Efficient feature combination techniques for emotional speech classification , 2016, International Journal of Speech Technology.