After more than 70 years of evolution, great achievements have been made in machine
translation. Especially in recent years, translation quality has been greatly improved with the …

The fast advancement in machine translation models necessitates the development of
accurate evaluation metrics that would allow researchers to track the progress in text …

Large-scale automatic speech translation systems today lack key features that help machine-
mediated communication feel seamless when compared to human-to-human dialogue. In …

Simultaneous machine translation begins to translate each source sentence before the
source speaker is finished speaking, with applications to live and streaming scenarios …

Simultaneous machine translation models start generating a target sequence before they
have encoded or read the source sequence. Recent approaches for this task either apply a …

In this work, we develop SimulSpeech, an end-to-end simultaneous speech to text
translation system which translates speech in source language to text in target language …

Abstract Machine translation (MT) is a technique that leverages computers to translate
human languages automatically. Nowadays, neural machine translation (NMT) which …

Simultaneous machine translation consists in starting output generation before the entire
input sequence is available. Wait-k decoders offer a simple but efficient approach for this …

Simultaneous translation is widely useful but remains challenging. Previous work falls into
two main categories:(a) fixed-latency policies such as Ma et al.(2019) and (b) adaptive …

Decoder-only large language models (LLMs) have recently demonstrated impressive
capabilities in text generation and reasoning. Nonetheless, they have limited applications in …