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

23 citations · 44 across the 16 of their papers we have counts for

collaborators
Showing 2019Show all

5 papers · 1 filter

cs.CR2019★ 23 cited

Adversarial Music: Real World Audio Adversary Against Wake-word Detection System

Juncheng B. Li, Shuhui Qu, Xinjian Li +3

Voice Assistants (VAs) such as Amazon Alexa or Google Assistant rely on wake-word detection to respond to people's commands, which could potentially be vulnerable to audio adversar…

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

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…