5 citations · 9 across the 5 of their papers we have counts for
5 papers
Approximate Nearest Neighbour Phrase Mining for Contextual Speech Recognition
Maurits Bleeker, Pawel Swietojanski, Stefan Braun +1
This paper presents an extension to train end-to-end Context-Aware Transformer Transducer ( CATT ) models by using a simple, yet efficient method of mining hard negative phrases fr…
Variable Attention Masking for Configurable Transformer Transducer Speech Recognition
Pawel Swietojanski, Stefan Braun, Dogan Can +9
This work studies the use of attention masking in transformer transducer based speech recognition for building a single configurable model for different deployment scenarios. We pr…
Exploring Retraining-Free Speech Recognition for Intra-sentential Code-Switching
Zhen Huang, Xiaodan Zhuang, Daben Liu +3
In this paper, we present our initial efforts for building a code-switching (CS) speech recognition system leveraging existing acoustic models (AMs) and language models (LMs), i.e.…
Frame-level SpecAugment for Deep Convolutional Neural Networks in Hybrid ASR Systems
Xinwei Li, Yuanyuan Zhang, Xiaodan Zhuang +1
Inspired by SpecAugment -- a data augmentation method for end-to-end ASR systems, we propose a frame-level SpecAugment method (f-SpecAugment) to improve the performance of deep con…
SNDCNN: Self-normalizing deep CNNs with scaled exponential linear units for speech recognition
Zhen Huang, Tim Ng, Leo Liu +3
Very deep CNNs achieve state-of-the-art results in both computer vision and speech recognition, but are difficult to train. The most popular way to train very deep CNNs is to use s…