10 citations · 18 across the 12 of their papers we have counts for
15 papers
Beyond Decodability: Do Acoustic Factors Drive Predictions in Speech-Based Alzheimer's Assessment?
Serli Kopar, Alkis Koudounas, Roshan P. Rane +3
Speech-based Alzheimer's disease (AD) assessments increasingly rely on pretrained self-supervised learning (SSL) models that learn acoustic representations directly from raw audio,…
Kraken: LLM-based Speech-to-Speech Translation via Low-bitrate VQ and Dual-path Source Conditioning
Hayato Futami, Hassan Shahmohammadi, Tushar Dhyani +5
Speech-to-speech translation (S2ST) has advanced significantly with speech LLMs, offering the potential for joint optimization and preserving non-linguistic information. However, t…
Benchmarking Speech-to-Speech Translation Models
Alkis Koudounas, Hayato Futami, Quentin Jodelet +3
Speech-to-speech translation (S2ST) has advanced rapidly, but offline evaluation lacks a unified protocol: studies report non-overlapping metric subsets, preventing direct comparis…
FAME: Fictional Actors for Multilingual Erasure
Claudio Savelli, Moreno La Quatra, Alkis Koudounas +1
LLMs trained on web-scale data raise concerns about privacy and the right to be forgotten. To address these issues, Machine Unlearning provides techniques to remove specific inform…
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…
A Concept-based approach to Voice Disorder Detection
Davide Ghia, Gabriele Ciravegna, Alkis Koudounas +4
Voice disorders affect a significant portion of the population, and the ability to diagnose them using automated, non-invasive techniques would represent a substantial advancement…
"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…
Exploring Generative Error Correction for Dysarthric Speech Recognition
Moreno La Quatra, Alkis Koudounas, Valerio Mario Salerno +1
Despite the remarkable progress in end-to-end Automatic Speech Recognition (ASR) engines, accurately transcribing dysarthric speech remains a major challenge. In this work, we prop…
MVP: Multi-source Voice Pathology detection
Alkis Koudounas, Moreno La Quatra, Gabriele Ciravegna +6
Voice disorders significantly impact patient quality of life, yet non-invasive automated diagnosis remains under-explored due to both the scarcity of pathological voice data, and t…
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…
"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…
voc2vec: A Foundation Model for Non-Verbal Vocalization
Alkis Koudounas, Moreno La Quatra, Marco Sabato Siniscalchi +1
Speech foundation models have demonstrated exceptional capabilities in speech-related tasks. Nevertheless, these models often struggle with non-verbal audio data, such as vocalizat…
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…
Voice Disorder Analysis: a Transformer-based Approach
Alkis Koudounas, Gabriele Ciravegna, Marco Fantini +4
Voice disorders are pathologies significantly affecting patient quality of life. However, non-invasive automated diagnosis of these pathologies is still under-explored, due to both…
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…