most citedEnforcing Encoder-Decoder Modularity in Sequence-to-Sequence Models

11 citations · 22 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20207 cited

Universal Phone Recognition with a Multilingual Allophone System

Xinjian Li, Siddharth Dalmia, Juncheng Li +8

Multilingual models can improve language processing, particularly for low resource situations, by sharing parameters across languages. Multilingual acoustic models, however, genera…

cs.CL2020

Towards Zero-shot Learning for Automatic Phonemic Transcription

Xinjian Li, Siddharth Dalmia, David R. Mortensen +3

Automatic phonemic transcription tools are useful for low-resource language documentation. However, due to the lack of training sets, only a tiny fraction of languages have phonemi…

cs.CL201911 cited

Enforcing Encoder-Decoder Modularity in Sequence-to-Sequence Models

Siddharth Dalmia, Abdelrahman Mohamed, Mike Lewis +2

Inspired by modular software design principles of independence, interchangeability, and clarity of interface, we introduce a method for enforcing encoder-decoder modularity in seq2…

cs.CL20194 cited

The ARIEL-CMU Systems for LoReHLT18

Aditi Chaudhary, Siddharth Dalmia, Junjie Hu +27

This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery a…

cs.CL2019

Phoneme Level Language Models for Sequence Based Low Resource ASR

Siddharth Dalmia, Xinjian Li, Alan W Black +1

Building multilingual and crosslingual models help bring different languages together in a language universal space. It allows models to share parameters and transfer knowledge acr…