Before revision:  The main aim of the challenge is to evaluate new technologies for text-dependent speaker verification (TD-SV) . There is one more task in the SdSVC which is text-independent speaker verification which is explained in a separate description file. The evaluation dataset in the challenge is recently released multi-purpose DeepMine dataset. The dataset has three parts and among them part1 is for text-dependent speaker verification .
After revision:  The main aim of the challenge is to evaluate new technologies for text-dependent speaker verification (TD-SV) . There is one more task in the SdSVC which is text-independent (TI) speaker verification (SV) in a short duration scenario. The proposed challenge evaluates SdSV with varying degree of phonetic overlap between the enrollment and test utterances (cross-lingual). It is the first challenge with a broad focus on systematic benchmark and analysis on varying degrees of phonetic variability on short-duration speaker recognition. We expect that modern methods (deep neural networks in particular) will play a key role .