Speaker Information using Subsegmental and Segmental Analysis of LP Residual

Self Determining Speaker Recognition by Three Level Segmental Processing Of Linear Prediction Residual

This paper proposes a speaker specific source information at different levels.speaker recognition system exploits the source information (LP residual) present at different levels namely subsegmental, segmental &suprasegmental. The subsegmental analysis considers LP residual in blocks of 5 msec with shift of 2.5 msec to extract speaker information. The segmental analysis extracts speaker informa...

Subsegmental, Segmental and Suprasegmental Features for Speaker Recognition Using Gaussian Mixture Model

In the feature extraction stage, features representing speaker information are extracted from the speech signal. In the present study LP residual derived from the speech data is used for training and testing and also processing of LP residual in time domain at subsegmental, segmental and suprasegmental levels. In the training phase, GMMs are built, one for each speaker, using the training data ...

Features for speaker and language identification

Abstract In this paper we examine several features derived from the speech signal for the purpose of identification of speaker or language from the speech signal. Most of the current systems for speaker and language identification use spectral features from short segments of speech. There are additional features which can be derived from the residual of the speech signal, which correspond to th...

Subsegmental, Segmental and Suprasegmental Features for Speaker Recognition Using Ergodic Hidden Markov Model

Time -frequency analysis of vocal source signal for speaker recognition

This paper investigates the importance of spectrotemporal characteristics of the source excitation signal for speaker recognition. We propose an effective feature extraction technique for obtaining essential timefrequency information from the linear prediction (LP) residual signal, which are closely related to the glottal excitation of individual speaker. With pitch synchronous analysis, wavele...