Text-dependent speaker verification: Classifiers, databases and RSR2015

Abstract

The RSR2015 database, designed to evaluate text-dependent speaker verification systems under different durations and lexical constraints has been collected and released by the Human Language Technology (HLT) department at Institute for Infocomm Research (I2R) in Singapore. English speakers were recorded with a balanced diversity of accents commonly found in Singapore. More than 151 h of speech data were recorded using mobile devices. The pool of speakers consists of 300 participants (143 female and 157 male speakers) between 17 and 42 years old making the RSR2015 database one of the largest publicly available database targeted for text-dependent speaker verification. We provide evaluation protocol for each of the three parts of the database, together with the results of two speaker verification system: the HiLAM system, based on a three layer acoustic architecture, and an i-vector/PLDA system. We thus provide a reference evaluation scheme and a reference performance on RSR2015 database to the research community. The HiLAM outperforms the state-of-the-art i-vector system in most of the scenarios.