Doroteo Torre Toledano

TL;DR: The most frequently used approach-based on a modified Hidden Markov Model (HMM) phonetic recognizer is analyzed, and a general framework for the local refinement of boundaries is proposed, and the performance of several pattern classification approaches is compared within this framework.

TL;DR: The acquisition setup and protocol are outlined, the contents of the corpus-including data and population statistics-are described, and the database will be publicly available for research purposes by mid-2006.

TL;DR: It is shown how the evaluation of DNA evidence, which is based on a probabilistic similarity-typicality metric in the form of likelihood ratios (LR), can also be generalized to continuous LR estimation, thus providing a common framework for phonetic-linguistic methods and automatic systems.

TL;DR: A new multimodal biometric database, acquired in the framework of the BiosecurID project, is presented together with the description of the acquisition setup and protocol and features such as: realistic acquisition scenario, balanced gender and population distributions, availability of information about particular demographic groups, and compatibility with other existing databases.

TL;DR: An open-source, end-to-end, LSTM RNN system running on limited computational resources (a single GPU) that outperforms a reference i-vector system on a subset of the NIST Language Recognition Evaluation (8 target languages, 3s task) by up to a 26%.