Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Eliya Nachmani"'
Publikováno v:
PLoS Computational Biology, Vol 20, Iss 1, p e1011678 (2024)
Reinforcement learning (RL) models are used extensively to study human behavior. These rely on normative models of behavior and stress interpretability over predictive capabilities. More recently, neural network models have emerged as a descriptive m
Externí odkaz:
https://doaj.org/article/6e406c1a0c9745f79cabf94ca129bd9e
Reinforcement learning (RL) models are used extensively to study human behavior. These rely on normative models of behavior and stress interpretability over predictive capabilities. More recently, neural network models have emerged as a descriptive m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1d13bc68af6f314a83aafec8d103d7b
https://doi.org/10.1101/2023.04.21.537666
https://doi.org/10.1101/2023.04.21.537666
We present a novel way of conditioning a pretrained denoising diffusion speech model to produce speech in the voice of a novel person unseen during training. The method requires a short (~3 seconds) sample from the target person, and generation is st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cdcec97956cbf0b38133b64f2d610a3a
http://arxiv.org/abs/2206.02246
http://arxiv.org/abs/2206.02246
Autor:
Eliya Nachmani, Yair Be'ery
The problem of maximum likelihood decoding with a neural decoder for error-correcting code is considered. It is shown that the neural decoder can be improved with two novel loss terms on the node's activations. The first loss term imposes a sparse co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e48b0322df7ee6e3053c2c4ee3bed9d3
http://arxiv.org/abs/2206.00786
http://arxiv.org/abs/2206.00786
Publikováno v:
MultiMedia Modeling ISBN: 9783030983574
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::578c88fe38747e5635512036f14c6fc3
https://doi.org/10.1007/978-3-030-98358-1_44
https://doi.org/10.1007/978-3-030-98358-1_44
Publikováno v:
Interspeech 2021.
Single channel speech separation has experienced great progress in the last few years. However, training neural speech separation for a large number of speakers (e.g., more than 10 speakers) is out of reach for the current methods, which rely on the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b71cd843dac86ba66368d5e887d83fe
https://doi.org/10.21437/interspeech.2021-493
https://doi.org/10.21437/interspeech.2021-493
Autor:
Eliya Nachmani, Lior Wolf
Publikováno v:
ICASSP
Hypernetworks were recently shown to improve the performance of message passing algorithms for decoding error correcting codes. In this work, we demonstrate how hypernetworks can be applied to decode polar codes by employing a new formalization of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c306654066abcf45f31cfdaa0433ba7
https://doi.org/10.1109/icassp40776.2020.9054607
https://doi.org/10.1109/icassp40776.2020.9054607
Publikováno v:
ICASSP
We present a unified network for voice separation of an unknown number of speakers. The proposed approach is composed of several separation heads optimized together with a speaker classification branch. The separation is carried out in the time domai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2ba31dec2e161623c04773068e01d83
Most existing deep learning based binaural speaker separation systems focus on producing a monaural estimate for each of the target speakers, and thus do not preserve the interaural cues, which are crucial for human listeners to perform sound localiz
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09367ae29996918056bf992179f3b845
Autor:
Lior Wolf, Eliya Nachmani
Publikováno v:
ICASSP
We present a TTS neural network that is able to produce speech in multiple languages. The proposed network is able to transfer a voice, which was presented as a sample in a source language, into one of several target languages. Training is done witho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f6b28c25cb8e56016b6d7fb23c91cf9
https://doi.org/10.1109/icassp.2019.8683519
https://doi.org/10.1109/icassp.2019.8683519