most citedA Contrastive Learning Approach to Mitigate Bias in Speech Models

5 citations · 8 across the 10 of their papers we have counts for

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cs.CL2025

Hallucination Benchmark for Speech Foundation Models

Alkis Koudounas, Moreno La Quatra, Manuel Giollo +2

Hallucinations in automatic speech recognition (ASR) systems refer to fluent and coherent transcriptions produced by neural ASR models that are completely unrelated to the underlyi…

cs.CL2025

"KAN you hear me?" Exploring Kolmogorov-Arnold Networks for Spoken Language Understanding

Alkis Koudounas, Moreno La Quatra, Eliana Pastor +2

Kolmogorov-Arnold Networks (KANs) have recently emerged as a promising alternative to traditional neural architectures, yet their application to speech processing remains under exp…

cs.CL2025

DeepDialogue: A Multi-Turn Emotionally-Rich Spoken Dialogue Dataset

Alkis Koudounas, Moreno La Quatra, Elena Baralis

Recent advances in conversational AI have demonstrated impressive capabilities in single-turn responses, yet multi-turn dialogues remain challenging for even the most sophisticated…

cs.CL2025★ 2 cited

"Alexa, can you forget me?" Machine Unlearning Benchmark in Spoken Language Understanding

Alkis Koudounas, Claudio Savelli, Flavio Giobergia +1

Machine unlearning, the process of efficiently removing specific information from machine learning models, is a growing area of interest for responsible AI. However, few studies ha…

cs.CL2024★ 1 cited

Speech Analysis of Language Varieties in Italy

Moreno La Quatra, Alkis Koudounas, Elena Baralis +1

Italy exhibits rich linguistic diversity across its territory due to the distinct regional languages spoken in different areas. Recent advances in self-supervised learning provide…

cs.CL2024★ 5 cited

A Contrastive Learning Approach to Mitigate Bias in Speech Models

Alkis Koudounas, Flavio Giobergia, Eliana Pastor +1

Speech models may be affected by performance imbalance in different population subgroups, raising concerns about fair treatment across these groups. Prior attempts to mitigate unfa…