1 citations · 1 across the 4 of their papers we have counts for
4 papers
Personalization of CTC-based End-to-End Speech Recognition Using Pronunciation-Driven Subword Tokenization
Zhihong Lei, Ernest Pusateri, Shiyi Han +8
Recent advances in deep learning and automatic speech recognition have improved the accuracy of end-to-end speech recognition systems, but recognition of personal content such as c…
Acoustic Model Fusion for End-to-end Speech Recognition
Zhihong Lei, Mingbin Xu, Shiyi Han +8
Recent advances in deep learning and automatic speech recognition (ASR) have enabled the end-to-end (E2E) ASR system and boosted the accuracy to a new level. The E2E systems implic…
Neural Language Model Pruning for Automatic Speech Recognition
Leonardo Emili, Thiago Fraga-Silva, Ernest Pusateri +2
We study model pruning methods applied to Transformer-based neural network language models for automatic speech recognition. We explore three aspects of the pruning frame work, nam…
Space-Efficient Representation of Entity-centric Query Language Models
Christophe Van Gysel, Mirko Hannemann, Ernest Pusateri +2
Virtual assistants make use of automatic speech recognition (ASR) to help users answer entity-centric queries. However, spoken entity recognition is a difficult problem, due to the…