4 papers
Self-Supervised Test-Time Tuning for Packet Loss Concealment
Yehoshua Dissen, Joseph Keshet
Packet loss concealment (PLC) reconstructs audio packets that are missing at the receiver, usually with a trained model whose parameters remain fixed at deployment time. This treat…
Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logits
Gilad Nurko, Roi Benita, Yehoshua Dissen +4
Robust classification in noisy environments remains a fundamental challenge in machine learning. Standard approaches typically treat signal enhancement and classification as separa…
HebDB: a Weakly Supervised Dataset for Hebrew Speech Processing
Arnon Turetzky, Or Tal, Yael Segal-Feldman +9
We present HebDB, a weakly supervised dataset for spoken language processing in the Hebrew language. HebDB offers roughly 2500 hours of natural and spontaneous speech recordings in…
Enhanced ASR Robustness to Packet Loss with a Front-End Adaptation Network
Yehoshua Dissen, Shiry Yonash, Israel Cohen +1
In the realm of automatic speech recognition (ASR), robustness in noisy environments remains a significant challenge. Recent ASR models, such as Whisper, have shown promise, but th…