4 papers
PatchDSU: Uncertainty Modeling for Out of Distribution Generalization in Keyword Spotting
Bronya Roni Chernyak, Yael Segal, Yosi Shrem +1
Deep learning models excel at many tasks but rely on the assumption that training and test data follow the same distribution. This assumption often does not hold in real-world spee…
UmbraTTS: Adapting Text-to-Speech to Environmental Contexts with Flow Matching
Neta Glazer, Aviv Navon, Yael Segal +6
Recent advances in Text-to-Speech (TTS) have enabled highly natural speech synthesis, yet integrating speech with complex background environments remains challenging. We introduce…
Whisper in Medusa's Ear: Multi-head Efficient Decoding for Transformer-based ASR
Yael Segal-Feldman, Aviv Shamsian, Aviv Navon +2
Large transformer-based models have significant potential for speech transcription and translation. Their self-attention mechanisms and parallel processing enable them to capture c…
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…