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Super-Human Performance in Online Low-latency Recognition of Conversational Speech
Achieving super-human performance in recognizing human speech has been a...
10/07/2020 ∙ by Thai-Son Nguyen, et al. ∙
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Relative Positional Encoding for Speech Recognition and Direct Translation
Transformer models are powerful sequence-to-sequence architectures that ...
05/20/2020 ∙ by Ngoc-Quan Pham, et al. ∙
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High Performance Sequence-to-Sequence Model for Streaming Speech Recognition
Recently sequence-to-sequence models have started to achieve state-of-th...
03/22/2020 ∙ by Thai-Son Nguyen, et al. ∙
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Low Latency ASR for Simultaneous Speech Translation
User studies have shown that reducing the latency of our simultaneous le...
03/22/2020 ∙ by Thai-Son Nguyen, et al. ∙
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Improving sequence-to-sequence speech recognition training with on-the-fly data augmentation
Sequence-to-Sequence (S2S) models recently started to show state-of-the-...
10/29/2019 ∙ by Thai-Son Nguyen, et al. ∙
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Learning Shared Encoding Representation for End-to-End Speech Recognition Models
In this work, we learn a shared encoding representation for a multi-task...
03/31/2019 ∙ by Thai-Son Nguyen, et al. ∙
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Using multi-task learning to improve the performance of acoustic-to-word and conventional hybrid models
Acoustic-to-word (A2W) models that allow direct mapping from acoustic si...
02/02/2019 ∙ by Thai-Son Nguyen, et al. ∙
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Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop
We summarize the accomplishments of a multi-disciplinary workshop explor...
02/14/2018 ∙ by Odette Scharenborg, et al. ∙
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