Investigating the use of modulation spectral features within an i-vector framework for far-field automatic speaker verification
Anderson Raymundo Avila, Francisco J. Fraga, Milton Sarria-Paja, Tiago Henrique Falk · 2014
It is known that channel variability compromises automatic speaker recognition accuracy. However, little attention has been given so far to the detrimental effects encountered under reverberant environments. In this paper, we focus on the issue of automatic speaker verification (ASV) under several levels of room reverberation. Alternative auditory inspired features are explored. Specifically, we investigate whether the performance of the so-called modulation spectral features (MSFs) can overcome the well-known mel-frequency cepstral coefficients (MFCCs). Experiments were conducted with an ASV system based on the state-of-the-art i-vector. The main contribution of this paper is to verify if MSFs combined with i-vectors are able to present the same performance encountered in the literature regarding speech recognition and speaker identification systems in reverberant environment.