Translate Smart, not Hard: Cascaded Translation Systems with Quality-Aware Deferral
Larger models often outperform smaller ones but come with high computational costs. Cascading offers a potential solution. By default, it uses smaller models and defers only some instances to larger, more powerful models. However, designing effective deferral rules remains a challenge. In this paper, we propose a simple yet effective approach for machine translation, using existing quality estimation (QE) metrics as deferral rules. We show that QE-based deferral allows a cascaded system to match the performance of a larger model while invoking it for a small fraction (30% to 50%) of the examples, significantly reducing computational costs. We validate this approach through both automatic and human evaluation.
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationSimilar Papers 제목 키워드 기반
TranSmart: A Practical Interactive Machine Translation System
Automatic machine translation is super efficient to produce translations yet their quality is not guaranteed. This technique report introduces TranSmart, a practical human-machine interactive translation system that is a…
Machine TranslationSentenceTranslationThe USTC-NELSLIP Offline Speech Translation Systems for IWSLT 2022
This paper describes USTC-NELSLIP’s submissions to the IWSLT 2022 Offline Speech Translation task, including speech translation of talks from English to German, English to Chinese and English to Japanese. We describe bot…
TranslationUsing Spoken Word Posterior Features in Neural Machine Translation
A spoken language translation (ST) system consists of at least two modules: an automatic speech recognition (ASR) system and a machine translation (MT) system. In most cases, an MT is only trained and optimized using err…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Machine TranslationNMT+3Improving Cascaded Unsupervised Speech Translation with Denoising Back-translation
Most of the speech translation models heavily rely on parallel data, which is hard to collect especially for low-resource languages. To tackle this issue, we propose to build a cascaded speech translation system without …
DenoisingMachine TranslationTranslationDirect Simultaneous Speech-to-Text Translation Assisted by Synchronized Streaming ASR
Simultaneous speech-to-text translation is widely useful in many scenarios. The conventional cascaded approach uses a pipeline of streaming ASR followed by simultaneous MT, but suffers from error propagation and extra la…
Simultaneous Speech-to-Text TranslationSpeech-to-TextSpeech-to-Text TranslationTranslation