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Language-agnostic Multilingual Modeling
Multilingual Automated Speech Recognition (ASR) systems allow for the jo...
04/20/2020 ∙ by Arindrima Datta, et al. ∙
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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...
03/28/2020 ∙ by Tara N. Sainath, et al. ∙
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A comparison of end-to-end models for long-form speech recognition
End-to-end automatic speech recognition (ASR) models, including both att...
11/06/2019 ∙ by Chung-Cheng Chiu, et al. ∙
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Large-Scale Multilingual Speech Recognition with a Streaming End-to-End Model
Multilingual end-to-end (E2E) models have shown great promise in expansi...
09/11/2019 ∙ by Anjuli Kannan, et al. ∙
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Extracting Symptoms and their Status from Clinical Conversations
This paper describes novel models tailored for a new application, that o...
06/05/2019 ∙ by Nan Du, et al. ∙
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Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Lingvo is a Tensorflow framework offering a complete solution for collab...
02/21/2019 ∙ by Jonathan Shen, et al. ∙
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Model Unit Exploration for Sequence-to-Sequence Speech Recognition
We evaluate attention-based encoder-decoder models along two dimensions:...
02/05/2019 ∙ by Kazuki Irie, et al. ∙
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Streaming End-to-end Speech Recognition For Mobile Devices
End-to-end (E2E) models, which directly predict output character sequenc...
11/15/2018 ∙ by Yanzhang He, et al. ∙
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Deep context: end-to-end contextual speech recognition
In automatic speech recognition (ASR) what a user says depends on the pa...
08/07/2018 ∙ by Golan Pundak, et al. ∙
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A Comparison of Techniques for Language Model Integration in Encoder-Decoder Speech Recognition
Attention-based recurrent neural encoder-decoder models present an elega...
07/27/2018 ∙ by Shubham Toshniwal, et al. ∙
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An analysis of incorporating an external language model into a sequence-to-sequence model
Attention-based sequence-to-sequence models for automatic speech recogni...
12/06/2017 ∙ by Anjuli Kannan, et al. ∙
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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 ...
12/05/2017 ∙ by Tara N. Sainath, et al. ∙
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Minimum Word Error Rate Training for Attention-based Sequence-to-Sequence Models
Sequence-to-sequence models, such as attention-based models in automatic...
12/05/2017 ∙ by Rohit Prabhavalkar, et al. ∙
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Improving the Performance of Online Neural Transducer Models
Having a sequence-to-sequence model which can operate in an online fashi...
12/05/2017 ∙ by Tara N. Sainath, et al. ∙
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State-of-the-art Speech Recognition With Sequence-to-Sequence Models
Attention-based encoder-decoder architectures such as Listen, Attend, an...
12/05/2017 ∙ by Chung-Cheng Chiu, et al. ∙
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Speech recognition for medical conversations
In this paper we document our experiences with developing speech recogni...
11/20/2017 ∙ by Chung-Cheng Chiu, et al. ∙
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Adversarial Evaluation of Dialogue Models
The recent application of RNN encoder-decoder models has resulted in sub...
01/27/2017 ∙ by Anjuli Kannan, et al. ∙
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Smart Reply: Automated Response Suggestion for Email
In this paper we propose and investigate a novel end-to-end method for a...
06/15/2016 ∙ by Anjuli Kannan, et al. ∙
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