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06/13/2023
Efficient Adapters for Giant Speech Models
Large pre-trained speech models are widely used as the de-facto paradigm...
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03/02/2023
Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages
We introduce the Universal Speech Model (USM), a single large model that...
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10/31/2022
Textless Direct Speech-to-Speech Translation with Discrete Speech Representation
Research on speech-to-speech translation (S2ST) has progressed rapidly i...
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05/16/2022
Accented Speech Recognition: Benchmarking, Pre-training, and Diverse Data
Building inclusive speech recognition systems is a crucial step towards ...
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02/03/2022
Self-supervised Learning with Random-projection Quantizer for Speech Recognition
We present a simple and effective self-supervised learning approach for ...
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10/30/2021
Cross-attention conformer for context modeling in speech enhancement for ASR
This work introduces cross-attention conformer, an attention-based archi...
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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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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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04/07/2021
Pushing the Limits of Non-Autoregressive Speech Recognition
We combine recent advancements in end-to-end speech recognition to non-a...
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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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11/11/2020
Efficient Knowledge Distillation for RNN-Transducer Models
Knowledge Distillation is an effective method of transferring knowledge ...
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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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10/22/2020
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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05/19/2020
Improved Noisy Student Training for Automatic Speech Recognition
Recently, a semi-supervised learning method known as "noisy student trai...
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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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12/11/2019
SpecAugment on Large Scale Datasets
Recently, SpecAugment, an augmentation scheme for automatic speech recog...
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11/21/2019
Speech Sentiment Analysis via Pre-trained Features from End-to-end ASR Models
In this paper, we propose to use pre-trained features from end-to-end AS...
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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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10/24/2019
Recognizing long-form speech using streaming end-to-end models
All-neural end-to-end (E2E) automatic speech recognition (ASR) systems t...
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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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04/18/2019
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
We present SpecAugment, a simple data augmentation method for speech rec...
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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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11/05/2018
Leveraging Weakly Supervised Data to Improve End-to-End Speech-to-Text Translation
End-to-end Speech Translation (ST) models have many potential advantages...
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07/27/2018
A Comparison of Techniques for Language Model Integration in Encoder-Decoder Speech Recognition
Attention-based recurrent neural encoder-decoder models present an elega...
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12/14/2017
Monotonic Chunkwise Attention
Sequence-to-sequence models with soft attention have been successfully a...
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12/05/2017
No Need for a Lexicon? Evaluating the Value of the Pronunciation Lexica in End-to-End Models
For decades, context-dependent phonemes have been the dominant sub-word ...
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12/05/2017
Minimum Word Error Rate Training for Attention-based Sequence-to-Sequence Models
Sequence-to-sequence models, such as attention-based models in automatic...
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12/05/2017
Improving the Performance of Online Neural Transducer Models
Having a sequence-to-sequence model which can operate in an online fashi...
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12/05/2017
State-of-the-art Speech Recognition With Sequence-to-Sequence Models
Attention-based encoder-decoder architectures such as Listen, Attend, an...
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11/20/2017
Speech recognition for medical conversations
In this paper we document our experiences with developing speech recogni...
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06/16/2017
An online sequence-to-sequence model for noisy speech recognition
Generative models have long been the dominant approach for speech recogn...
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05/16/2017
Learning Hard Alignments with Variational Inference
There has recently been significant interest in hard attention models fo...
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08/03/2016