19 citations · 38 across the 10 of their papers we have counts for
12 papers
Virtual Consistency for Audio Editing
Matthieu Cervera, Francesco Paissan, Mirco Ravanelli +1
Free-form, text-based audio editing remains a persistent challenge, despite progress in inversion-based neural methods. Current approaches rely on slow inversion procedures, limiti…
First Results on the Search for Lepton Number Violating Neutrinoless Double Beta Decay with the LEGEND-200 Experiment
H. Acharya, N. Ackermann, M. Agostini +256
The LEGEND collaboration is searching for neutrinoless double beta () decay by operating high-purity germanium detectors enriched in Ge in a low-background liquid argo…
FocalCodec: Low-Bitrate Speech Coding via Focal Modulation Networks
Luca Della Libera, Francesco Paissan, Cem Subakan +1
Large language models have revolutionized natural language processing through self-supervised pretraining on massive datasets. Inspired by this success, researchers have explored a…
Investigating the Effectiveness of Explainability Methods in Parkinson's Detection from Speech
Eleonora Mancini, Francesco Paissan, Paolo Torroni +2
Speech impairments in Parkinson's disease (PD) provide significant early indicators for diagnosis. While models for speech-based PD detection have shown strong performance, their i…
LMAC-TD: Producing Time Domain Explanations for Audio Classifiers
Eleonora Mancini, Francesco Paissan, Mirco Ravanelli +1
Neural networks are typically black-boxes that remain opaque with regards to their decision mechanisms. Several works in the literature have proposed post-hoc explanation methods t…
Open-Source Conversational AI with SpeechBrain 1.0
Mirco Ravanelli, Titouan Parcollet, Adel Moumen +30
SpeechBrain is an open-source Conversational AI toolkit based on PyTorch, focused particularly on speech processing tasks such as speech recognition, speech enhancement, speaker re…
Listenable Maps for Zero-Shot Audio Classifiers
Francesco Paissan, Luca Della Libera, Mirco Ravanelli +1
Interpreting the decisions of deep learning models, including audio classifiers, is crucial for ensuring the transparency and trustworthiness of this technology. In this paper, we…
Listenable Maps for Audio Classifiers
Francesco Paissan, Mirco Ravanelli, Cem Subakan
Despite the impressive performance of deep learning models across diverse tasks, their complexity poses challenges for interpretation. This challenge is particularly evident for au…
Audio Editing with Non-Rigid Text Prompts
Francesco Paissan, Luca Della Libera, Zhepei Wang +3
In this paper, we explore audio-editing with non-rigid text edits. We show that the proposed editing pipeline is able to create audio edits that remain faithful to the input audio.…
Scaling strategies for on-device low-complexity source separation with Conv-Tasnet
Mohamed Nabih Ali, Francesco Paissan, Daniele Falavigna +1
Recently, several very effective neural approaches for single-channel speech separation have been presented in the literature. However, due to the size and complexity of these mode…
Posthoc Interpretation via Quantization
Francesco Paissan, Cem Subakan, Mirco Ravanelli
In this paper, we introduce a new approach, called Posthoc Interpretation via Quantization (PIQ), for interpreting decisions made by trained classifiers. Our method utilizes vector…
The Front-End electronics for the liquid Argon instrumentation of the LEGEND-200 experiment
I. Abritta Costa, A. Budano, N. Burlac +3
In this paper we provide a detailed technical description of the Front-End (FE) electronics for the liquid Argon instrumentation of the LEGEND-200 experiment, searching for the ver…