The MITLL-AFRL IWSLT 2016 Systems
This report summarizes the MITLL-AFRL MT and ASR systems and the experiments run during the 2016 IWSLT evaluation campaign. Building on lessons learned from previous years’ results, we refine our ASR systems and examine the explosion of neural machine translation systems and techniques developed in the past year. We experiment with a variety of phrase-based, hierarchical and neural-network approaches in machine translation and utilize system combination to create a composite system with the best characteristics of all attempted MT approaches.
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationTranslationSimilar Papers 제목 키워드 기반
The AFRL-MITLL WMT16 News-Translation Task Systems
The AFRL-MITLL WMT17 Systems: Old, New, Borrowed, BLEU
The AFRL-MITLL WMT15 System: There's More than One Way to Decode It!
The AFRL IWSLT 2018 Systems: What Worked, What Didn’t
This report summarizes the Air Force Research Laboratory (AFRL) machine translation (MT) and automatic speech recognition (ASR) systems submitted to the spoken language translation (SLT) and low-resource MT tasks as part…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Machine Translationspeech-recognition+2The AFRL IWSLT 2020 Systems: Work-From-Home Edition
This report summarizes the Air Force Research Laboratory (AFRL) submission to the offline spoken language translation (SLT) task as part of the IWSLT 2020 evaluation campaign. As in previous years, we chose to adopt the …
Action DetectionActivity DetectionAutomatic Speech RecognitionAutomatic Speech Recognition (ASR)+9