Significance of glottal activity detection for speaker verification in degraded and limited data condition

The objective of this work is to establish the importance of speaker information present in the glottal regions of speech signal. In addition, its robustness for degraded data and significance for limited data is sought for the task of speaker verification. An adaptive threshold method is proposed to use on zero frequency filtered signal to get the glottal activity regions. Feature vectors are extracted from regions having significant glottal activity. An i-vector based speaker verification system is developed using NIST SRE 2003 database and the performance of proposed method is evaluated in degraded and limited data condition. Robustness of proposed method is tested for white and babble noise. Further, short utterances of test data are considered to evaluate the performance in limited data condition. The proposed method based on the selection of glottal regions is found to perform better than the baseline energy based voice activity detection method in degraded and limited data conditions.