activity
20182023
most citedAdversarial Music: Real World Audio Adversary Against Wake-word Detection System

23 citations · 48 across the 20 of their papers we have counts for

collaborators
Showing cs.CLShow all

15 papers · 1 filter

cs.CL2022★ 1 cited

Textless Direct Speech-to-Speech Translation with Discrete Speech Representation

Xinjian Li, Ye Jia, Chung-Cheng Chiu

Research on speech-to-speech translation (S2ST) has progressed rapidly in recent years. Many end-to-end systems have been proposed and show advantages over conventional cascade sys…

cs.CL2022

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…

cs.CL2021

Phoneme Recognition through Fine Tuning of Phonetic Representations: a Case Study on Luhya Language Varieties

Kathleen Siminyu, Xinjian Li, Antonios Anastasopoulos +3

Models pre-trained on multiple languages have shown significant promise for improving speech recognition, particularly for low-resource languages. In this work, we focus on phoneme…

cs.CL2021

Tusom2021: A Phonetically Transcribed Speech Dataset from an Endangered Language for Universal Phone Recognition Experiments

David R. Mortensen, Jordan Picone, Xinjian Li +1

There is growing interest in ASR systems that can recognize phones in a language-independent fashion. There is additionally interest in building language technologies for low-resou…

cs.CL2020

Acoustics Based Intent Recognition Using Discovered Phonetic Units for Low Resource Languages

Akshat Gupta, Xinjian Li, Sai Krishna Rallabandi +1

With recent advancements in language technologies, humans are now speaking to devices. Increasing the reach of spoken language technologies requires building systems in local langu…

cs.CL2020★ 1 cited

A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization

Graham Neubig, Shruti Rijhwani, Alexis Palmer +21

Despite recent advances in natural language processing and other language technology, the application of such technology to language documentation and conservation has been limited…

cs.CL2020★ 2 cited

AlloVera: A Multilingual Allophone Database

David R. Mortensen, Xinjian Li, Patrick Littell +6

We introduce a new resource, AlloVera, which provides mappings from 218 allophones to phonemes for 14 languages. Phonemes are contrastive phonological units, and allophones are the…

cs.CL2020★ 7 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.CL2019

SANTLR: Speech Annotation Toolkit for Low Resource Languages

Xinjian Li, Zhong Zhou, Siddharth Dalmia +2

While low resource speech recognition has attracted a lot of attention from the speech community, there are a few tools available to facilitate low resource speech collection. In t…

cs.CL2019★ 3 cited

Multilingual Speech Recognition with Corpus Relatedness Sampling

Xinjian Li, Siddharth Dalmia, Alan W. Black +1

Multilingual acoustic models have been successfully applied to low-resource speech recognition. Most existing works have combined many small corpora together and pretrained a multi…

cs.CL2019★ 4 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…

cs.CL2018

Real-time Neural-based Input Method

Jiali Yao, Raphael Shu, Xinjian Li +2

The input method is an essential service on every mobile and desktop devices that provides text suggestions. It converts sequential keyboard inputs to the characters in its target…

cs.CL2018

Domain Robust Feature Extraction for Rapid Low Resource ASR Development

Siddharth Dalmia, Xinjian Li, Florian Metze +1

Developing a practical speech recognizer for a low resource language is challenging, not only because of the (potentially unknown) properties of the language, but also because test…