19 citations · 24 across the 7 of their papers we have counts for
8 papers
Cross-lingual Knowledge Transfer and Iterative Pseudo-labeling for Low-Resource Speech Recognition with Transducers
Jan Silovsky, Liuhui Deng, Arturo Argueta +6
Voice technology has become ubiquitous recently. However, the accuracy, and hence experience, in different languages varies significantly, which makes the technology not equally in…
Neural Transducer Training: Reduced Memory Consumption with Sample-wise Computation
Stefan Braun, Erik McDermott, Roger Hsiao
The neural transducer is an end-to-end model for automatic speech recognition (ASR). While the model is well-suited for streaming ASR, the training process remains challenging. Dur…
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…
Optimizing Bilingual Neural Transducer with Synthetic Code-switching Text Generation
Thien Nguyen, Nathalie Tran, Liuhui Deng +16
Code-switching describes the practice of using more than one language in the same sentence. In this study, we investigate how to optimize a neural transducer based bilingual automa…
Bilingual End-to-End ASR with Byte-Level Subwords
Liuhui Deng, Roger Hsiao, Arnab Ghoshal
In this paper, we investigate how the output representation of an end-to-end neural network affects multilingual automatic speech recognition (ASR). We study different representati…
Online Automatic Speech Recognition with Listen, Attend and Spell Model
Roger Hsiao, Dogan Can, Tim Ng +2
The Listen, Attend and Spell (LAS) model and other attention-based automatic speech recognition (ASR) models have known limitations when operated in a fully online mode. In this pa…
Improving Language Identification for Multilingual Speakers
Andrew Titus, Jan Silovsky, Nanxin Chen +3
Spoken language identification (LID) technologies have improved in recent years from discriminating largely distinct languages to discriminating highly similar languages or even di…
Migrating Monarch Butterfly Localization Using Multi-Sensor Fusion Neural Networks
Mingyu Yang, Roger Hsiao, Gordy Carichner +6
Details of Monarch butterfly migration from the U.S. to Mexico remain a mystery due to lack of a proper localization technology to accurately localize and track butterfly migration…