Learning from Human Interpreter Speech

Speaker: Matthias Paulik

Title: "Learning from Human Interpreter Speech"
Date: 12 August 2008

Abstract:
Can spoken language translation (SLT) profit from human interpreter speech? In this talk, we explore scenarios which involve live human interpretation, off-line transcription and off-line translation on a massive scale. We consider the deployment of machine translation (MT) and automatic speech recognition (ASR) for the off-line transcription and translation tasks; our systems are trained on 80+ hours of audio data and on parallel text corpora of ~40 million words. To improve performance, we use the available human interpreter speech as an auxiliary information source to bias ASR and MT language models. We evaluate this approach on European Parliament Plenary Session (EPPS) data in three languages (English, Spanish and German), and report preliminary improvements in translation and transcription performance.

Coupling of ASR+MT: Initial Experiments & Future Directions

Speaker: Ian Lane

Title: Tighter Coupling of ASR+MT: Initial Experiments & Future Directions

Abstract:
In this talk, I will first give a brief overview of my PhD work entitled "Flexible Spoken Language Understanding based on Topic Classification and Domain Detection", and describe how the proposed approaches can be applied to applications other than speech-to-speech translation. I will
then describe my current work which focuses on improving coupling between ASR and Machine-Translation Systems, specifically, when applied to conversational speech. Finally, I will propose future directions for which I hope to receive a large amount of feedback.

Speech Translation with Multiple Speech and Translation Hypotheses

Date: November 15, 2005

Presenter: Chiori Hori

Title: Speech Translation with Multiple Speech and Translation Hypotheses