6 citations · 7 across the 6 of their papers we have counts for
6 papers
Knowing What to Stress: A Discourse-Conditioned Text-to-Speech Benchmark
Arnon Turetzky, Avihu Dekel, Hagai Aronowitz +2
Spoken meaning often depends not only on what is said, but also on which word is emphasized. The same sentence can convey correction, contrast, or clarification depending on where…
Speech Synthesis From Continuous Features Using Per-Token Latent Diffusion
Arnon Turetzky, Avihu Dekel, Nimrod Shabtay +5
We present SALAD, a zero-shot TTS autoregressive model operating over continuous speech representations. SALAD utilizes a per-token diffusion process to refine and predict continuo…
LAST: Language Model Aware Speech Tokenization
Arnon Turetzky, Yossi Adi
Speech tokenization serves as the foundation of speech language model (LM), enabling them to perform various tasks such as spoken language modeling, text-to-speech, speech-to-text,…
A Language Modeling Approach to Diacritic-Free Hebrew TTS
Amit Roth, Arnon Turetzky, Yossi Adi
We tackle the task of text-to-speech (TTS) in Hebrew. Traditional Hebrew contains Diacritics, which dictate the way individuals should pronounce given words, however, modern Hebrew…
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…
Deep Audio Waveform Prior
Arnon Turetzky, Tzvi Michelson, Yossi Adi +1
Convolutional neural networks contain strong priors for generating natural looking images [1]. These priors enable image denoising, super resolution, and inpainting in an unsupervi…