Search Results for author: Eliya Nachmani

Found 32 papers, 11 papers with code

SimulTron: On-Device Simultaneous Speech to Speech Translation

no code implementations4 Jun 2024 Alex Agranovich, Eliya Nachmani, Oleg Rybakov, Yifan Ding, Ye Jia, Nadav Bar, Heiga Zen, Michelle Tadmor Ramanovich

Simultaneous speech-to-speech translation (S2ST) holds the promise of breaking down communication barriers and enabling fluid conversations across languages.

Simultaneous Speech-to-Speech Translation Speech-to-Speech Translation +1

Decision S4: Efficient Sequence-Based RL via State Spaces Layers

no code implementations8 Jun 2023 Shmuel Bar-David, Itamar Zimerman, Eliya Nachmani, Lior Wolf

Recently, sequence learning methods have been applied to the problem of off-policy Reinforcement Learning, including the seminal work on Decision Transformers, which employs transformers for this task.

Translatotron 3: Speech to Speech Translation with Monolingual Data

no code implementations27 May 2023 Eliya Nachmani, Alon Levkovitch, Yifan Ding, Chulayuth Asawaroengchai, Heiga Zen, Michelle Tadmor Ramanovich

This paper presents Translatotron 3, a novel approach to unsupervised direct speech-to-speech translation from monolingual speech-text datasets by combining masked autoencoder, unsupervised embedding mapping, and back-translation.

Speech-to-Speech Translation Translation

Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM

no code implementations24 May 2023 Eliya Nachmani, Alon Levkovitch, Roy Hirsch, Julian Salazar, Chulayuth Asawaroengchai, Soroosh Mariooryad, Ehud Rivlin, RJ Skerry-Ryan, Michelle Tadmor Ramanovich

Key to our approach is a training objective that jointly supervises speech recognition, text continuation, and speech synthesis using only paired speech-text pairs, enabling a `cross-modal' chain-of-thought within a single decoding pass.

Language Modelling Question Answering +3

Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation

no code implementations25 Jan 2023 Shahar Lutati, Eliya Nachmani, Lior Wolf

Applying a diffusion model Vocoder that was pretrained to model single-speaker voices on the output of a deterministic separation model leads to state-of-the-art separation results.

Audio Source Separation Generalization Bounds +2

Zero-Shot Voice Conditioning for Denoising Diffusion TTS Models

no code implementations5 Jun 2022 Alon Levkovitch, Eliya Nachmani, Lior Wolf

At the heart of the method lies a sampling process that combines the estimation of the denoising model with a low-pass version of the new speaker's sample.


Neural Decoding with Optimization of Node Activations

no code implementations1 Jun 2022 Eliya Nachmani, Yair Be'ery

The problem of maximum likelihood decoding with a neural decoder for error-correcting code is considered.


SepIt: Approaching a Single Channel Speech Separation Bound

no code implementations24 May 2022 Shahar Lutati, Eliya Nachmani, Lior Wolf

We present an upper bound for the Single Channel Speech Separation task, which is based on an assumption regarding the nature of short segments of speech.

Audio Source Separation Generalization Bounds +2

SegDiff: Image Segmentation with Diffusion Probabilistic Models

1 code implementation1 Dec 2021 Tomer Amit, Tal Shaharbany, Eliya Nachmani, Lior Wolf

Since the diffusion model is probabilistic, it is applied multiple times, and the results are merged into a final segmentation map.

Decoder Image Generation +3

A-Muze-Net: Music Generation by Composing the Harmony based on the Generated Melody

no code implementations25 Nov 2021 Or Goren, Eliya Nachmani, Lior Wolf

The Midi is represented in a way that is invariant to the musical scale, and the melody is represented, for the purpose of conditioning the harmony, by the content of each bar, viewed as a chord.

Music Generation

Zero-Shot Translation using Diffusion Models

no code implementations2 Nov 2021 Eliya Nachmani, Shaked Dovrat

In this work, we show a novel method for neural machine translation (NMT), using a denoising diffusion probabilistic model (DDPM), adjusted for textual data, following recent advances in the field.

Denoising Machine Translation +4

Denoising Diffusion Gamma Models

no code implementations10 Oct 2021 Eliya Nachmani, Robin San Roman, Lior Wolf

Generative diffusion processes are an emerging and effective tool for image and speech generation.


Non Gaussian Denoising Diffusion Models

1 code implementation14 Jun 2021 Eliya Nachmani, Robin San Roman, Lior Wolf

Moreover, we show that using a mixture of Gaussian noise variables in the diffusion process improves the performance over a diffusion process that is based on a single distribution.


Recovering AES Keys with a Deep Cold Boot Attack

no code implementations9 Jun 2021 Itamar Zimerman, Eliya Nachmani, Lior Wolf

In this work, we combine a novel cryptographic variant of a deep error correcting code technique with a modified SAT solver scheme to apply the attack on AES keys.

Cryptanalysis Scheduling

Noise Estimation for Generative Diffusion Models

no code implementations6 Apr 2021 Robin San-Roman, Eliya Nachmani, Lior Wolf

Generative diffusion models have emerged as leading models in speech and image generation.

Denoising Image Generation +1

Autoregressive Belief Propagation for Decoding Block Codes

no code implementations23 Jan 2021 Eliya Nachmani, Lior Wolf

We revisit recent methods that employ graph neural networks for decoding error correcting codes and employ messages that are computed in an autoregressive manner.

Single channel voice separation for unknown number of speakers under reverberant and noisy settings

2 code implementations4 Nov 2020 Shlomo E. Chazan, Lior Wolf, Eliya Nachmani, Yossi Adi

The proposed approach is composed of several separation heads optimized together with a speaker classification branch.

Classification General Classification

SAGRNN: Self-Attentive Gated RNN for Binaural Speaker Separation with Interaural Cue Preservation

1 code implementation2 Sep 2020 Ke Tan, Buye Xu, Anurag Kumar, Eliya Nachmani, Yossi Adi

In addition, our approach effectively preserves the interaural cues, which improves the accuracy of sound localization.

Audio and Speech Processing Sound

Voice Separation with an Unknown Number of Multiple Speakers

4 code implementations ICML 2020 Eliya Nachmani, Yossi Adi, Lior Wolf

We present a new method for separating a mixed audio sequence, in which multiple voices speak simultaneously.

Speech Separation

Molecule Property Prediction and Classification with Graph Hypernetworks

1 code implementation1 Feb 2020 Eliya Nachmani, Lior Wolf

In this work, we demonstrate that the replacement of the underlying networks with hypernetworks leads to a boost in performance, obtaining state of the art results in various benchmarks.

Classification General Classification +1

A Gated Hypernet Decoder for Polar Codes

no code implementations8 Nov 2019 Eliya Nachmani, Lior Wolf

Hypernetworks were recently shown to improve the performance of message passing algorithms for decoding error correcting codes.


Hyper-Graph-Network Decoders for Block Codes

1 code implementation NeurIPS 2019 Eliya Nachmani, Lior Wolf

Neural decoders were shown to outperform classical message passing techniques for short BCH codes.

Unsupervised Singing Voice Conversion

no code implementations13 Apr 2019 Eliya Nachmani, Lior Wolf

The proposed network is not conditioned on the text or on the notes, and it directly converts the audio of one singer to the voice of another.

Data Augmentation Decoder +1

Unsupervised Polyglot Text To Speech

no code implementations6 Feb 2019 Eliya Nachmani, Lior Wolf

We present a TTS neural network that is able to produce speech in multiple languages.

Fitting New Speakers Based on a Short Untranscribed Sample

no code implementations ICML 2018 Eliya Nachmani, Adam Polyak, Yaniv Taigman, Lior Wolf

Learning-based Text To Speech systems have the potential to generalize from one speaker to the next and thus require a relatively short sample of any new voice.

Speech Synthesis

Near Maximum Likelihood Decoding with Deep Learning

no code implementations8 Jan 2018 Eliya Nachmani, Yaron Bachar, Elad Marciano, David Burshtein, Yair Be'ery

The proposed decoder is based on the neural Belief Propagation algorithm and the Automorphism Group.


VoiceLoop: Voice Fitting and Synthesis via a Phonological Loop

2 code implementations ICLR 2018 Yaniv Taigman, Lior Wolf, Adam Polyak, Eliya Nachmani

We present a new neural text to speech (TTS) method that is able to transform text to speech in voices that are sampled in the wild.


Deep Learning Methods for Improved Decoding of Linear Codes

2 code implementations21 Jun 2017 Eliya Nachmani, Elad Marciano, Loren Lugosch, Warren J. Gross, David Burshtein, Yair Beery

Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.


RNN Decoding of Linear Block Codes

no code implementations24 Feb 2017 Eliya Nachmani, Elad Marciano, David Burshtein, Yair Be'ery

We also demonstrate improved performance over belief propagation on sparser Tanner graph representations of the codes.


Learning to Decode Linear Codes Using Deep Learning

3 code implementations16 Jul 2016 Eliya Nachmani, Yair Beery, David Burshtein

A novel deep learning method for improving the belief propagation algorithm is proposed.


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