DeepAI AI Chat
Log In Sign Up

Universal Simultaneous Machine Translation with Mixture-of-Experts Wait-k Policy

by   Shaolei Zhang, et al.
Institute of Computing Technology, Chinese Academy of Sciences

Simultaneous machine translation (SiMT) generates translation before reading the entire source sentence and hence it has to trade off between translation quality and latency. To fulfill the requirements of different translation quality and latency in practical applications, the previous methods usually need to train multiple SiMT models for different latency levels, resulting in large computational costs. In this paper, we propose a universal SiMT model with Mixture-of-Experts Wait-k Policy to achieve the best translation quality under arbitrary latency with only one trained model. Specifically, our method employs multi-head attention to accomplish the mixture of experts where each head is treated as a wait-k expert with its own waiting words number, and given a test latency and source inputs, the weights of the experts are accordingly adjusted to produce the best translation. Experiments on three datasets show that our method outperforms all the strong baselines under different latency, including the state-of-the-art adaptive policy.


page 1

page 2

page 3

page 4


Turning Fixed to Adaptive: Integrating Post-Evaluation into Simultaneous Machine Translation

Simultaneous machine translation (SiMT) starts its translation before re...

Gaussian Multi-head Attention for Simultaneous Machine Translation

Simultaneous machine translation (SiMT) outputs translation while receiv...

Data-Driven Adaptive Simultaneous Machine Translation

In simultaneous translation (SimulMT), the most widely used strategy is ...

A Mixture of h-1 Heads is Better than h Heads

Multi-head attentive neural architectures have achieved state-of-the-art...

Monotonic Multihead Attention

Simultaneous machine translation models start generating a target sequen...

Opportunistic Decoding with Timely Correction for Simultaneous Translation

Simultaneous translation has many important application scenarios and at...

Monotonic Infinite Lookback Attention for Simultaneous Machine Translation

Simultaneous machine translation begins to translate each source sentenc...