activity
20162026
most citedUnsupervised Cross-Domain Image Generation

429 citations · 1.1k across the 26 of their papers we have counts for

collaborators
Showing 2021Show all

8 papers · 1 filter

cs.CV2021

Locally Shifted Attention With Early Global Integration

Shelly Sheynin, Sagie Benaim, Adam Polyak +1

Recent work has shown the potential of transformers for computer vision applications. An image is first partitioned into patches, which are then used as input tokens for the attent…

cs.CL2021★ 4 cited

Textless Speech Emotion Conversion using Discrete and Decomposed Representations

Felix Kreuk, Adam Polyak, Jade Copet +7

Speech emotion conversion is the task of modifying the perceived emotion of a speech utterance while preserving the lexical content and speaker identity. In this study, we cast the…

eess.AS2021★ 4 cited

fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit

Changhan Wang, Wei-Ning Hsu, Yossi Adi +5

This paper presents fairseq S^2, a fairseq extension for speech synthesis. We implement a number of autoregressive (AR) and non-AR text-to-speech models, and their multi-speaker va…

cs.CL2021★ 16 cited

Text-Free Prosody-Aware Generative Spoken Language Modeling

Eugene Kharitonov, Ann Lee, Adam Polyak +8

Speech pre-training has primarily demonstrated efficacy on classification tasks, while its capability of generating novel speech, similar to how GPT-2 can generate coherent paragra…

cs.CL2021★ 7 cited

Direct speech-to-speech translation with discrete units

Ann Lee, Peng-Jen Chen, Changhan Wang +9

We present a direct speech-to-speech translation (S2ST) model that translates speech from one language to speech in another language without relying on intermediate text generation…

cs.SD2021★ 1 cited

Speech Resynthesis from Discrete Disentangled Self-Supervised Representations

Adam Polyak, Yossi Adi, Jade Copet +5

We propose using self-supervised discrete representations for the task of speech resynthesis. To generate disentangled representation, we separately extract low-bitrate representat…

cs.CL2021

Generative Spoken Language Modeling from Raw Audio

Kushal Lakhotia, Evgeny Kharitonov, Wei-Ning Hsu +8

We introduce Generative Spoken Language Modeling, the task of learning the acoustic and linguistic characteristics of a language from raw audio (no text, no labels), and a set of m…

cs.SD2021

High Fidelity Speech Regeneration with Application to Speech Enhancement

Adam Polyak, Lior Wolf, Yossi Adi +2

Speech enhancement has seen great improvement in recent years mainly through contributions in denoising, speaker separation, and dereverberation methods that mostly deal with envir…