Speaker Recognition System Using Symbolic Modelling of Voiceprint
Shanmukhappa A. Angadi, Sanjeevakumar M. Hatture · International Journal of Signal Processing Image Processing and Pattern Recognition · 2017
Voice biometric trait is used in speaker recognition system due to its combined behavioral and physiological characteristics.This paper presents a symbolic inference system for text-dependent speaker recognition system by exploring the physiological characteristics embedded in the user utterance.These characteristics also capture the user behaviour.The symbolic data object is constructed using different voiceprint features namely the inter-lexical pause position, complementary spectral features such as spectral entropy, spectral centroid and spectral flatness, pitch, loudness and formants.These features are explored in this work as inter-lexical pause position provides the articulation capability of user vocal tract.The spectral characteristics model the functional properties of the human ear and loudness feature provides the strength of ear's perception.The relation between physical and perceptual properties of sound is estimated through pitch whereas formants provide the acoustic reverberation of the human vocal tract.The variability in features of user/speaker utterance of words is represented with symbolic data.The speaker identification is performed using span, content and position symbolic similarity measures [6], modified for the current work.The proposed method is evaluated on 100 users of voice corpus of VTU-BEC-DB multimodal biometric database.The experimental results demonstrate an overall identification rate of 90.56%.Experimental results show that the symbolic data representation of voice features provides better speaker recognition.