38 citations · 137 across the 21 of their papers we have counts for
57 papers
Token-level Sequence Labeling for Spoken Language Understanding using Compositional End-to-End Models
Siddhant Arora, Siddharth Dalmia, Brian Yan +3
End-to-end spoken language understanding (SLU) systems are gaining popularity over cascaded approaches due to their simplicity and ability to avoid error propagation. However, thes…
SQuAT: Sharpness- and Quantization-Aware Training for BERT
Zheng Wang, Juncheng B Li, Shuhui Qu +2
Quantization is an effective technique to reduce memory footprint, inference latency, and power consumption of deep learning models. However, existing quantization methods suffer f…
CTC Alignments Improve Autoregressive Translation
Brian Yan, Siddharth Dalmia, Yosuke Higuchi +4
Connectionist Temporal Classification (CTC) is a widely used approach for automatic speech recognition (ASR) that performs conditionally independent monotonic alignment. However fo…
ASR2K: Speech Recognition for Around 2000 Languages without Audio
Xinjian Li, Florian Metze, David R Mortensen +2
Most recent speech recognition models rely on large supervised datasets, which are unavailable for many low-resource languages. In this work, we present a speech recognition pipeli…
On Adversarial Robustness of Large-scale Audio Visual Learning
Juncheng B Li, Shuhui Qu, Xinjian Li +2
As audio-visual systems are being deployed for safety-critical tasks such as surveillance and malicious content filtering, their robustness remains an under-studied area. Existing…
Differentiable Allophone Graphs for Language-Universal Speech Recognition
Brian Yan, Siddharth Dalmia, David R. Mortensen +2
Building language-universal speech recognition systems entails producing phonological units of spoken sound that can be shared across languages. While speech annotations at the lan…