7 papers · 1 filter
DialFork: Going Beyond Factuality to Evaluate Procedural Hallucination in Conversational Agents
Sergio Burdisso, Esaú Villatoro-Tello, Dairazalia Sánchez-Cortés +4
Large language models (LLMs) deployed as conversational agents are increasingly expected to follow procedural logic. While factual hallucination has received extensive attention, a…
Benchmarking Automatic Speech Recognition Tools for Iberian Languages
Fernando López, Pablo Gómez, David Solans +2
Comprehensive evaluations of automatic speech recognition (ASR) for Iberian languages remain limited, and low-resource languages, biases, and efficiency trade-offs are underexplore…
The Eloquence submission for Task 2 of the Interspeech 2026 MLC-SLM challenge
Jordi Luque, Lorenzo Concina, Marco Matassoni +2
This paper details the Eloquence team's approach to Task 2 of the 2nd MLC-SLM challenge at Interspeech 2026, which involves multilingual Multiple-Choice Question Answering (MCQA) a…
ESCUCHA: A Spanish Speech Benchmark for Heterogeneous Acoustic Conditions
Fernando López, Ana Ayala, Guillermo Segovia +4
As large audio language models (LALMs) advance, robust evaluation frameworks have become essential. In this context, Spanish speech understanding under realistic acoustic condition…
S-DiverSe: Spanish Diverse Speech
Fernando López, Fernando Ibañez, Ana Martínez +4
Automatic speech recognition (ASR) has advanced remarkably for standard speech, yet speech affected by neurological conditions remains a challenge. We present S-DiverSe (Spanish Di…
FiLM-Based Speaker Conditioning of a SpeechLLM for Pathological Speech Recognition
Fernando López, Santosh Kesiraju, Jordi Luque
Automatic speech recognition (ASR) has advanced remarkably for standard speech; however, pathological speech from neurological conditions remains a significant challenge. We invest…
"OK Aura, Be Fair With Me": Demographics-Agnostic Training for Bias Mitigation in Wake-up Word Detection
Fernando López, Paula Delgado-Santos, Pablo Gómez +2
Voice-based interfaces are widely used; however, achieving fair Wake-up Word detection across diverse speaker populations remains a critical challenge due to persistent demographic…