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Day: September 9, 2022

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Efficient Transformers for End-to-End Neural Speaker Diarization

September 9, 2022September 20, 2022 daniel

Speaker: Sergio Izquierdo. Abstract: The recently proposed End-to-End Neural speaker Diarization framework (EEND) handles speech overlap and speech activity detection natively. While extensions of this work have reported remarkable results in both two-speaker and multi-speaker diarization scenarios, these come at… Read More

AUDIAS Seminars

Sound Event Detection in a large-scale audio dataset with multi-resolution neural networks

September 9, 2022September 20, 2022 daniel

Speaker: Sara Barahona Quirós. Abstract: Sound event detection is the task that aims to automatize the human’s ability of recognizing sound events in the environment by their particular acoustic information. For this purpose, deep learning techniques are employed to build… Read More

AUDIAS Seminars

AUDIAS Seminars

Rigorous Forensic Automatic Speaker Recognition: Bayesian Decision Theory, Probabilistic Calibration and Case-Specific Validation

July 10, 2026

Speaker: Daniel Ramos. Abstract: The use of automatic speaker recognition…

FiLM-Based Speaker Conditioning of a SpeechLLM for Pathological Speech Recognition

July 3, 2026

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

Automatic Classification of Classical Music Composers from Audio Signals

July 2, 2026

Speaker: Sonia Aoi García Shida. Abstract: Automatic composer classification is…

Detection and Grouping of Accents within Rural Spanish

July 2, 2026

Speaker: Koral Tubia. Abstract: Rural Spanish preserves a rich dialectal…

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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

Rigorous Forensic Automatic Speaker Recognition: Bayesian Decision Theory, Probabilistic Calibration and Case-Specific Validation

July 10, 2026

FiLM-Based Speaker Conditioning of a SpeechLLM for Pathological Speech Recognition

July 3, 2026
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