research
∙
06/14/2023
TryOnDiffusion: A Tale of Two UNets
Given two images depicting a person and a garment worn by another person...
share
research
∙
02/08/2023
Noise2Music: Text-conditioned Music Generation with Diffusion Models
We introduce Noise2Music, where a series of diffusion models is trained ...
research
∙
12/20/2022
Character-Aware Models Improve Visual Text Rendering
Current image generation models struggle to reliably produce well-formed...
research
∙
10/06/2022
Novel View Synthesis with Diffusion Models
We present 3DiM, a diffusion model for 3D novel view synthesis, which is...
research
∙
10/05/2022
Imagen Video: High Definition Video Generation with Diffusion Models
We present Imagen Video, a text-conditional video generation system base...
research
∙
05/23/2022
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
We present Imagen, a text-to-image diffusion model with an unprecedented...
research
∙
04/07/2022
Video Diffusion Models
Generating temporally coherent high fidelity video is an important miles...
research
∙
02/11/2022
Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality
Diffusion models have emerged as an expressive family of generative mode...
research
∙
11/10/2021
Palette: Image-to-Image Diffusion Models
We introduce Palette, a simple and general framework for image-to-image ...
research
∙
09/27/2021
BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition
We summarize the results of a host of efforts using giant automatic spee...
research
∙
06/17/2021
WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis
This paper introduces WaveGrad 2, a non-autoregressive generative model ...
research
∙
06/07/2021
Learning to Efficiently Sample from Diffusion Probabilistic Models
Denoising Diffusion Probabilistic Models (DDPMs) have emerged as a power...
research
∙
04/15/2021
Image Super-Resolution via Iterative Refinement
We present SR3, an approach to image Super-Resolution via Repeated Refin...
research
∙
04/07/2021
Pushing the Limits of Non-Autoregressive Speech Recognition
We combine recent advancements in end-to-end speech recognition to non-a...
research
∙
04/05/2021
SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network
We present SpeechStew, a speech recognition model that is trained on a c...
research
∙
10/09/2020
Multichannel Generative Language Model: Learning All Possible Factorizations Within and Across Channels
A channel corresponds to a viewpoint or transformation of an underlying ...
research
∙
09/02/2020
WaveGrad: Estimating Gradients for Waveform Generation
This paper introduces WaveGrad, a conditional model for waveform generat...
research
∙
04/16/2020
Non-Autoregressive Machine Translation with Latent Alignments
This paper investigates two latent alignment models for non-autoregressi...
research
∙
02/20/2020
Imputer: Sequence Modelling via Imputation and Dynamic Programming
This paper presents the Imputer, a neural sequence model that generates ...
research
∙
01/15/2020
Insertion-Deletion Transformer
We propose the Insertion-Deletion Transformer, a novel transformer-based...
research
∙
12/11/2019
SpecAugment on Large Scale Datasets
Recently, SpecAugment, an augmentation scheme for automatic speech recog...
research
∙
10/29/2019
An Empirical Study of Generation Order for Machine Translation
In this work, we present an empirical study of generation order for mach...
research
∙
10/29/2019
Big Bidirectional Insertion Representations for Documents
The Insertion Transformer is well suited for long form text generation d...
research
∙
06/13/2019
Speaker-Targeted Audio-Visual Models for Speech Recognition in Cocktail-Party Environments
Speech recognition in cocktail-party environments remains a significant ...
research
∙
06/04/2019
KERMIT: Generative Insertion-Based Modeling for Sequences
We present KERMIT, a simple insertion-based approach to generative model...
research
∙
04/18/2019
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
We present SpecAugment, a simple data augmentation method for speech rec...
research
∙
02/21/2019
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Lingvo is a Tensorflow framework offering a complete solution for collab...
research
∙
02/08/2019
Insertion Transformer: Flexible Sequence Generation via Insertion Operations
We present the Insertion Transformer, an iterative, partially autoregres...
research
∙
12/07/2018
Privacy Partitioning: Protecting User Data During the Deep Learning Inference Phase
We present a practical method for protecting data during the inference p...
research
∙
11/22/2018
Bytes are All You Need: End-to-End Multilingual Speech Recognition and Synthesis with Bytes
We present two end-to-end models: Audio-to-Byte (A2B) and Byte-to-Audio ...
research
∙
10/02/2018
Optimal Completion Distillation for Sequence Learning
We present Optimal Completion Distillation (OCD), a training procedure f...
research
∙
06/08/2017
Advances in Joint CTC-Attention based End-to-End Speech Recognition with a Deep CNN Encoder and RNN-LM
We present a state-of-the-art end-to-end Automatic Speech Recognition (A...
research
∙
10/10/2016
Latent Sequence Decompositions
We present the Latent Sequence Decompositions (LSD) framework. LSD decom...
research
∙
10/10/2016
Very Deep Convolutional Networks for End-to-End Speech Recognition
Sequence-to-sequence models have shown success in end-to-end speech reco...
research
∙
08/05/2015
Listen, Attend and Spell
We present Listen, Attend and Spell (LAS), a neural network that learns ...
research
∙
04/07/2015
Transferring Knowledge from a RNN to a DNN
Deep Neural Network (DNN) acoustic models have yielded many state-of-the...
research
∙
04/07/2015