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 …

Recent research shows a big convergence in model architecture, training objectives, and
inference methods across various tasks for different modalities. In this paper, we propose …

What does it take to create the Babel Fish, a tool that can help individuals translate speech
between any two languages? While recent breakthroughs in text-based models have …

We present a direct speech-to-speech translation (S2ST) model that translates speech from
one language to speech in another language without relying on intermediate text …

We present an attention-based sequence-to-sequence neural network which can directly
translate speech from one language into speech in another language, without relying on an …

Direct speech-to-speech translation (S2ST) translates speech from one language into
another using a single model. However, due to the presence of linguistic and acoustic …

Direct speech-to-speech translation (S2ST), in which all components can be optimized
jointly, is advantageous over cascaded approaches to achieve fast inference with a …

Direct speech-to-speech translation (S2ST) models suffer from data scarcity issues as there
exists little parallel S2ST data, compared to the amount of data available for conventional …

Direct speech-to-speech translation (S2ST) with discrete units leverages recent progress in
speech representation learning. Specifically, a sequence of discrete representations derived …

We propose PolyVoice, a language model-based framework for speech-to-speech
translation (S2ST) system. Our framework consists of two language models: a translation …