2 citations · 2 across the 3 of their papers we have counts for
5 papers
Probabilistic Fusion and Calibration of Neural Speaker Diarization Models
Juan Ignacio Alvarez-Trejos, Sergio A. Balanya, Daniel Ramos +1
End-to-End Neural Diarization (EEND) systems produce frame-level probabilistic speaker activity estimates, yet since evaluation focuses primarily on Diarization Error Rate (DER), t…
ORCA: Open-ended Response Correctness Assessment for Audio Question Answering
Šimon Sedláček, Sara Barahona, Bolaji Yusuf +9
Reliable assessment of the abilities of large audio language models (LALMs) is essential to advancing the state of the art. As benchmarks rapidly evolve to incorporate complex reas…
MMAU-Pro: A Challenging and Comprehensive Benchmark for Holistic Evaluation of Audio General Intelligence
Sonal Kumar, Šimon Sedláček, Vaibhavi Lokegaonkar +31
Audio comprehension-including speech, non-speech sounds, and music-is essential for achieving human-level intelligence. Consequently, AI agents must demonstrate holistic audio unde…
Leveraging Speaker Embeddings in End-to-End Neural Diarization for Two-Speaker Scenarios
Juan Ignacio Alvarez-Trejos, Beltrán Labrador, Alicia Lozano-Diez
End-to-end neural speaker diarization systems are able to address the speaker diarization task while effectively handling speech overlap. This work explores the incorporation of sp…
Personalizing Keyword Spotting with Speaker Information
Beltrán Labrador, Pai Zhu, Guanlong Zhao +5
Keyword spotting systems often struggle to generalize to a diverse population with various accents and age groups. To address this challenge, we propose a novel approach that integ…