Speaker: Vicente Jose Escarigo Miranda Abstract: Anuran vocalizations are valuable for biodiversity monitoring, but their automatic analysis is challenging because multiple species often vocalize simultaneously and class distributions are highly imbalanced. AnuraSet provides expert annotations for 42 Neotropical species together… Read More
Prediction of HIF Binding Sites
Speaker: Elias Boudjella. Abstract: This presentation describes a deep learning approach for predicting HIF binding sites from DNA sequences. It begins with the biological background and the construction of the datasets using ATAC-seq and ChIP-seq data from different cell types.… Read More
Rigorous Forensic Automatic Speaker Recognition: Bayesian Decision Theory, Probabilistic Calibration and Case-Specific Validation
Speaker: Daniel Ramos. Abstract: The use of automatic speaker recognition systems in forensic science has undergone a dramatic improvement in recent years in terms of scientific rigor, objectivity, and consensus. As a result, the discipline has become strongly aligned with… Read More
FiLM-Based Speaker Conditioning of a SpeechLLM for Pathological Speech Recognition
Speaker: William Fernando López Gavilanez. Abstract: Automatic speech recognition (ASR) has advanced remarkably for standard speech; however, pathological speech from neurological conditions remains a significant challenge. We investigate speaker conditioning via Feature-wise Linear Modulation (FiLM), injecting x-vector-derived information into each… Read More
Automatic Classification of Classical Music Composers from Audio Signals
Speaker: Sonia Aoi García Shida. Abstract: Automatic composer classification is a challenging task within the field of Music Information Retrieval, as it requires identifying compositional styles between composers from the same musical period, unlike genre classification where differences between classes… Read More
Detection and Grouping of Accents within Rural Spanish
Speaker: Koral Tubia. Abstract: Rural Spanish preserves a rich dialectal diversity that has received little attention form a computational point of view, partly because most speech processing systems are trained on standard, urban speech. In this work, we use the… Read More