1 citations · 1 across the 3 of their papers we have counts for
3 papers
eess.AS2026
Fully Differentiable Neural Forced Alignment via Soft Dynamic Programming
Rotem Rousso, Eyal Cohen, Joseph Keshet
Recent advances in sequence modeling have significantly improved ASR systems, bringing them close to human-level recognition accuracy and enhancing robustness across diverse acoust…
cs.CL2024
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…
eess.AS2024★ 1 cited
Tradition or Innovation: A Comparison of Modern ASR Methods for Forced Alignment
Rotem Rousso, Eyal Cohen, Joseph Keshet +1
Forced alignment (FA) plays a key role in speech research through the automatic time alignment of speech signals with corresponding text transcriptions. Despite the move towards en…