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Day: January 1, 2019

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Daniel Ramos visits the Machine Learning Group at the University of Cambridge

January 1, 2019July 1, 2020 audias

Daniel Ramos visited the Machine Learning Group at the University of Cambridge for a research stay from January to May 2019 funded by the Spanish Ministry of Education, to work on probabilistic approaches to likelihood ratio computation in forensic glass… Read More

Highlights, News & Events

AUDIAS starts a new project funded by the Spanish Ministry of Science, Innovation and Universities (grant RTI2018-098091-B-I00)

January 1, 2019July 1, 2020 audias

AUDIAS starts the new project “Aprendizaje Profundo en Voz para Aplicaciones Forenses y de Seguridad“, funded by the Spanish Ministry of Science, Innovation and Universities under grant RTI2018-098091-B-I00. The project will run from Jan. 2019 to Dec. 2021.

Highlights, News & Events

AUDIAS Seminars

Attention-Based Ensemble Systems for Component-Level Audio Deepfake Detection in the ESDD2 Challenge

November 13, 2026

Speaker: Alejandro Delgado Montero. Abstract: The recent Environment-Aware Speech and…

From Supervised Prediction to Unsupervised Discovery: Decoding Latent Epigenetic States via Multi-Omic Manifold Learning

November 6, 2026

Speaker: Alfonso Rincón Pérez. Abstract: Bridging chromatin architecture to transcriptional…

S-DiverSe: Spanish Diverse Speech

October 16, 2026

Speaker: William Fernando López Gavilánez. Abstract: Automatic speech recognition (ASR)…

Transformer-Based Automatic Music Transcription for Piano with Noise Robustness and Mobile Deployment

October 9, 2026

Speaker: Miguel Fernández Lara. Abstract: This work presents the development…

About AUDIAS

AUDIAS is a solid research group addressing challenging problems in speech, audio and temporal signals from deep foundations in machine learning and signal processing.

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Highlights

Attention-Based Ensemble Systems for Component-Level Audio Deepfake Detection in the ESDD2 Challenge

November 13, 2026

From Supervised Prediction to Unsupervised Discovery: Decoding Latent Epigenetic States via Multi-Omic Manifold Learning

November 6, 2026
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