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09/18/2023
Instruction-Following Speech Recognition
Conventional end-to-end Automatic Speech Recognition (ASR) models primar...
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09/08/2023
Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts
Sparse Mixture-of-Experts models (MoEs) have recently gained popularity ...
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03/31/2023
Practical Conformer: Optimizing size, speed and flops of Conformer for on-Device and cloud ASR
Conformer models maintain a large number of internal states, the vast ma...
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08/29/2022
A Language Agnostic Multilingual Streaming On-Device ASR System
On-device end-to-end (E2E) models have shown improvements over a convent...
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03/23/2022
Pathways: Asynchronous Distributed Dataflow for ML
We present the design of a new large scale orchestration layer for accel...
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03/09/2022
Sentence-Select: Large-Scale Language Model Data Selection for Rare-Word Speech Recognition
Language model fusion helps smart assistants recognize words which are r...
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12/14/2021
Co-training Transformer with Videos and Images Improves Action Recognition
In learning action recognition, models are typically pre-trained on obje...
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10/09/2021
Vector-quantized Image Modeling with Improved VQGAN
Pretraining language models with next-token prediction on massive text c...
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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...
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08/07/2021
W2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training
Motivated by the success of masked language modeling (MLM) in pre-traini...
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05/10/2021
GSPMD: General and Scalable Parallelization for ML Computation Graphs
We present GSPMD, an automatic, compiler-based parallelization system fo...
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04/30/2021
Scaling End-to-End Models for Large-Scale Multilingual ASR
Building ASR models across many language families is a challenging multi...
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04/25/2021
Bridging the gap between streaming and non-streaming ASR systems bydistilling ensembles of CTC and RNN-T models
Streaming end-to-end automatic speech recognition (ASR) systems are wide...
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02/10/2021
Searching for Fast Model Families on Datacenter Accelerators
Neural Architecture Search (NAS), together with model scaling, has shown...
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01/27/2021
Transformer Based Deliberation for Two-Pass Speech Recognition
Interactive speech recognition systems must generate words quickly while...
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11/21/2020
A Better and Faster End-to-End Model for Streaming ASR
End-to-end (E2E) models have shown to outperform state-of-the-art conven...
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10/27/2020
Cascaded encoders for unifying streaming and non-streaming ASR
End-to-end (E2E) automatic speech recognition (ASR) models, by now, have...
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10/24/2020
Unsupervised Learning of Disentangled Speech Content and Style Representation
We present an approach for unsupervised learning of speech representatio...
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10/22/2020
Improving Streaming Automatic Speech Recognition With Non-Streaming Model Distillation On Unsupervised Data
Streaming end-to-end automatic speech recognition (ASR) models are widel...
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10/21/2020
FastEmit: Low-latency Streaming ASR with Sequence-level Emission Regularization
Streaming automatic speech recognition (ASR) aims to emit each hypothesi...
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10/20/2020
Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition
We employ a combination of recent developments in semi-supervised learni...
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10/12/2020
Universal ASR: Unify and Improve Streaming ASR with Full-context Modeling
Streaming automatic speech recognition (ASR) aims to emit each hypothesi...
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08/30/2020
Parallel Rescoring with Transformer for Streaming On-Device Speech Recognition
Recent advances of end-to-end models have outperformed conventional mode...
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08/24/2020
Improving Tail Performance of a Deliberation E2E ASR Model Using a Large Text Corpus
End-to-end (E2E) automatic speech recognition (ASR) systems lack the dis...
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05/16/2020
Dynamic Sparsity Neural Networks for Automatic Speech Recognition
In automatic speech recognition (ASR), model pruning is a widely adopted...
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05/16/2020
Conformer: Convolution-augmented Transformer for Speech Recognition
Recently Transformer and Convolution neural network (CNN) based models h...
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05/07/2020
RNN-T Models Fail to Generalize to Out-of-Domain Audio: Causes and Solutions
In recent years, all-neural end-to-end approaches have obtained state-of...
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05/07/2020
ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context
Convolutional neural networks (CNN) have shown promising results for end...
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03/28/2020
A Streaming On-Device End-to-End Model Surpassing Server-Side Conventional Model Quality and Latency
Thus far, end-to-end (E2E) models have not been shown to outperform stat...
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03/24/2020
BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models
Neural architecture search (NAS) has shown promising results discovering...
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03/17/2020
Deliberation Model Based Two-Pass End-to-End Speech Recognition
End-to-end (E2E) models have made rapid progress in automatic speech rec...
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11/20/2019
EfficientDet: Scalable and Efficient Object Detection
Model efficiency has become increasingly important in computer vision. I...
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11/06/2019
A comparison of end-to-end models for long-form speech recognition
End-to-end automatic speech recognition (ASR) models, including both att...
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08/29/2019
Two-Pass End-to-End Speech Recognition
The requirements for many applications of state-of-the-art speech recogn...
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06/12/2019
Monotonic Infinite Lookback Attention for Simultaneous Machine Translation
Simultaneous machine translation begins to translate each source sentenc...
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05/06/2019
Searching for MobileNetV3
We present the next generation of MobileNets based on a combination of c...
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04/16/2019
NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection
Current state-of-the-art convolutional architectures for object detectio...
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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...
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11/16/2018
Domain Adaptive Transfer Learning with Specialist Models
Transfer learning is a widely used method to build high performing compu...
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11/15/2018
Streaming End-to-end Speech Recognition For Mobile Devices
End-to-end (E2E) models, which directly predict output character sequenc...
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10/16/2018
Hierarchical Generative Modeling for Controllable Speech Synthesis
This paper proposes a neural end-to-end text-to-speech (TTS) model which...
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07/31/2018
MnasNet: Platform-Aware Neural Architecture Search for Mobile
Designing convolutional neural networks (CNN) models for mobile devices ...
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06/12/2018
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
We describe a neural network-based system for text-to-speech (TTS) synth...
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12/16/2017
