We introduce and demonstrate how to effectively train multilingual machi...
Expressive speech-to-speech translation (S2ST) aims to transfer prosodic...
Language models are defined over a finite set of inputs, which creates a...
BibleTTS is a large, high-quality, open speech dataset for ten languages...
The Universal Morphology (UniMorph) project is a collaborative effort
pr...
What are the units of text that we want to model? From bytes to multi-wo...
Speech-to-speech translation combines machine translation with speech
sy...
While there exist scores of natural languages, each with its unique feat...
While language identification is a fundamental speech and language proce...
Machine translation models have discrete vocabularies and commonly use
s...
We present the Multilingual TEDx corpus, built to support speech recogni...
Typological knowledge bases (KBs) such as WALS (Dryer and Haspelmath, 20...
A broad goal in natural language processing (NLP) is to develop a system...
A major hurdle in data-driven research on typology is having sufficient ...
End-to-end models for speech translation (ST) more tightly couple speech...
Transformer models are powerful sequence-to-sequence architectures that ...
Prior work has explored directly regularizing the output distributions o...
This paper presents the submission by the CMU-01 team to the SIGMORPHON ...
Previous work on end-to-end translation from speech has primarily used
f...
Spoken language translation applications for speech suffer due to
conver...
When translating from speech, special consideration for conversational s...
In neural machine translation (NMT), it is has become standard to transl...