66 citations · 140 across the 11 of their papers we have counts for
14 papers
Flexi-Transducer: Optimizing Latency, Accuracy and Compute forMulti-Domain On-Device Scenarios
Jay Mahadeokar, Yangyang Shi, Yuan Shangguan +7
Often, the storage and computational constraints of embeddeddevices demand that a single on-device ASR model serve multiple use-cases / domains. In this paper, we propose aFlexible…
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…
Semantic Distance: A New Metric for ASR Performance Analysis Towards Spoken Language Understanding
Suyoun Kim, Abhinav Arora, Duc Le +4
Word Error Rate (WER) has been the predominant metric used to evaluate the performance of automatic speech recognition (ASR) systems. However, WER is sometimes not a good indicator…
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…
Improving RNN Transducer Based ASR with Auxiliary Tasks
Chunxi Liu, Frank Zhang, Duc Le +3
End-to-end automatic speech recognition (ASR) models with a single neural network have recently demonstrated state-of-the-art results compared to conventional hybrid speech recogni…
Alignment Restricted Streaming Recurrent Neural Network Transducer
Jay Mahadeokar, Yuan Shangguan, Duc Le +6
There is a growing interest in the speech community in developing Recurrent Neural Network Transducer (RNN-T) models for automatic speech recognition (ASR) applications. RNN-T is t…