55 citations · 74 across the 11 of their papers we have counts for
6 papers · 1 filter
Dynamic Encoder Transducer: A Flexible Solution For Trading Off Accuracy For Latency
Yangyang Shi, Varun Nagaraja, Chunyang Wu +9
We propose a dynamic encoder transducer (DET) for on-device speech recognition. One DET model scales to multiple devices with different computation capacities without retraining or…
Contextualized Streaming End-to-End Speech Recognition with Trie-Based Deep Biasing and Shallow Fusion
Duc Le, Mahaveer Jain, Gil Keren +9
How to leverage dynamic contextual information in end-to-end speech recognition has remained an active research area. Previous solutions to this problem were either designed for sp…
Deep Shallow Fusion for RNN-T Personalization
Duc Le, Gil Keren, Julian Chan +3
End-to-end models in general, and Recurrent Neural Network Transducer (RNN-T) in particular, have gained significant traction in the automatic speech recognition community in the l…
Streaming Attention-Based Models with Augmented Memory for End-to-End Speech Recognition
Ching-Feng Yeh, Yongqiang Wang, Yangyang Shi +4
Attention-based models have been gaining popularity recently for their strong performance demonstrated in fields such as machine translation and automatic speech recognition. One m…
Transformer in action: a comparative study of transformer-based acoustic models for large scale speech recognition applications
Yongqiang Wang, Yangyang Shi, Frank Zhang +4
In this paper, we summarize the application of transformer and its streamable variant, Emformer based acoustic model for large scale speech recognition applications. We compare the…
Just ASK: Building an Architecture for Extensible Self-Service Spoken Language Understanding
Anjishnu Kumar, Arpit Gupta, Julian Chan +9
This paper presents the design of the machine learning architecture that underlies the Alexa Skills Kit (ASK) a large scale Spoken Language Understanding (SLU) Software Development…