40 citations · 109 across the 27 of their papers we have counts for
8 papers · 2 filters
Align, Write, Re-order: Explainable End-to-End Speech Translation via Operation Sequence Generation
Motoi Omachi, Brian Yan, Siddharth Dalmia +2
The black-box nature of end-to-end speech translation (E2E ST) systems makes it difficult to understand how source language inputs are being mapped to the target language. To solve…
A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding
Yifan Peng, Siddhant Arora, Yosuke Higuchi +6
Collecting sufficient labeled data for spoken language understanding (SLU) is expensive and time-consuming. Recent studies achieved promising results by using pre-trained models in…
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…
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…
Two-Pass Low Latency End-to-End Spoken Language Understanding
Siddhant Arora, Siddharth Dalmia, Xuankai Chang +3
End-to-end (E2E) models are becoming increasingly popular for spoken language understanding (SLU) systems and are beginning to achieve competitive performance to pipeline-based app…
Branchformer: Parallel MLP-Attention Architectures to Capture Local and Global Context for Speech Recognition and Understanding
Yifan Peng, Siddharth Dalmia, Ian Lane +1
Conformer has proven to be effective in many speech processing tasks. It combines the benefits of extracting local dependencies using convolutions and global dependencies using sel…