Speaker: Alicia Lozano-Diez. Abstract: In this talk, I will review a few of the last trends in speaker diarization and target speaker ASR. I will present two papers that address these two tasks respectively, and leverage the power of foundational… Read More
What can LLMs bring to the field of acoustic event detection?
Speaker: Sergio Segovia González. Abstract: The answer to this question through these two articles, “WILDDESED: An LLM-POWERED dataset for wild domestic environment sound event detection system” and “Leveraging LLM and Text-Queried Separation for Noise-Robust Sound Event Detection” has been carried… Read More
Exploring Large Protein Language Models in Constrained Data Regimes
Speaker: Manuel Fernando Mollon Laorca. Abstract: In this study, we expand upon the FLIP benchmark—designed for evaluating protein language models (pLMs) in small, specialized prediction tasks—by assessing the performance of state-of-the-art models, including ESM-2, SaProt, and Tranception, on the FLIP… Read More
Fusion-Based Speaker Diarization: Insights from IberSpeech2024
Speaker: Juan Ignacio Álvarez Trejos. Abstract: This talk presents the results of our participation in the speaker diarization challenge at IberSpeech2024. Our approach combines the strengths of three diarization models: a custom-trained Diaper model, Pyannote, and VBx, through an innovative… Read More
Device-robust audio classification
Speaker: Wiliam Fernando López Gavilánez. Abstract: Audio classifiers designed for deployment across diverse devices often face unforeseen conditions during inference, attributable to device-specific characteristics. These challenges stem from variations in microphone transfer functions or on-chip digital signal pre-processing, which result… Read More
Towards Efficient Conformer-based Sound Event Detection
Speaker: Sara Barahona Quirós. Abstract: The Conformer architecture has shown excellent performance in accurately classifying sound events but lacks temporal precision when predicting time boundaries. While increasing the length of the input sequences can mitigate this issue, it also increases… Read More
Analysis of Speaker Label Matching for Diarization of Long Audios on RTVE2022 Dataset
Speaker: Laura Herrera Alarcón. Abstract: This study introduces an algorithm to match predicted speaker labels from short audio segments into a final prediction. This involves extracting an x-vector for each speaker in each segment and applying constrained Agglomerative Clustering to… Read More
Analyzing DiaPer EEND Speaker Diarization Models on the RTVE2022 Dataset
Speaker: Juan Ignacio Álvarez Trejos. Abstract: The task of speaker diarization has lately been successfully tackled with end-to-end neural diarization (EEND) models instead of modular cascaded ones. Among them, the very new EEND Perceiver-based attractors (DiaPer) comes with a light… Read More
Automatic Speech Recognition in Dialectal Data (COSER)
Speaker: Clara Adsuar Ávila. Abstract: In this project, we address the importance of enhancing the accessibility and usefulness of Deep Learning technologies for non-standard speakers. From a linguistic perspective, rural Spanish areas are rich in dialectal variety. However, most technology… Read More
Emotion recognition in Spanish audio
Speaker: Manuel Otero González. Abstract: En esta charla se explicará la tarea de reconocimiento de emociones en audios en español, presentando los enfoques más avanzados del estado del arte, como Wav2Vec2 y W2V-Bert. Además, se introducirá el reto EmoSPeech, cuyo… Read More