Speech Translation

When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as well as from a purely technological side. This paper describes the SCATE research with respect to improved fuzzy matching, parallel treebanks, the integration of translation memories with machine translation, quality estimation, terminology extraction from comparable texts, the use of speech recognition in the translation process, and human computer interaction and interface design for the professional translation environment. For each of these topics, we describe the experiments we performed and the conclusions drawn, providing an overview of the highlights of the entire SCATE project.

Speech-to-speech translation technology has difficulties processing elements of spontaneity in conversation. We propose a discourse marker attribute in speech corpora to help overcome some of these problems. There have already been some attempts to annotate discourse markers in speech corpora. However, as there is no consistency on what expressions count as discourse markers, we have to reconsider how to set a framework for annotating, and, in order to better understand what we gain by introducing a discourse marker category, we have to analyse their characteristics and functions in discourse. This is especially important for languages such as Slovenian where no or little research on the topic of discourse markers has been carried out. The aims of this paper are to present a scheme for annotating discourse markers based on the analysis of a corpus of telephone conversations in the tourism domain in the Slovenian language, and to give some additional arguments based on the characteristics and functions of discourse markers that confirm their special status in conversation.

This paper presents the wireless network architecture to provide multilingual speech translation and local positioning system during Hajj operations. The pilgrims require low power, low cost and compact ear connected devices to receive the information in their native language. The proposed RF transceiver front-end design consists of multiple numbers of oscillators tuned within spectrum of 5-to-8.5GHz. In transmitting mode, oscillators

The aim of this paper is to help the communication of two people, one hearing impaired and one visually impaired by converting speech to fingerspelling and fingerspelling to speech. Fingerspelling is a subset of sign language, and uses finger signs to spell letters of the spoken or written language. We aim to convert finger spelled words to speech and vice versa. Different spoken languages and sign languages such as English, Russian, Turkish and Czech are considered.

Spoken communication across a language barrier is of increasing importance in both civilian and military applications. In this paper, we present an English/Iraqi Arabic speech-to-speech translation system for the military force protection domain (checkpoints, municipal ...

In this paper we will present our ongoing work on a plan-based discourse processor developed in the context of the Enthusiast Spanish to English translation system as part of the JANUS multi-lingual speech-to-speech translation system. We will demonstrate that theories of discourse which postulate a strict tree structure of discourse on either the intentional or attentional level are not totally

Coling 2008: Proceedings of the workshop on Speech Processing for Safety Critical Translation and Pervasive Applications, pages 32–35 Manchester, August 2008 The 2008 MedSLT System Manny Rayner 1, Pierrette Bouillon 1, Jane Brotanek 2, Glenn Flores 2 Sonia Halimi 1, ...

Named entity recognition is a preprocessing tool to many natural language processing tasks, such as text summarization, speech translation, and document categorization. Many systems for named entity recognition have been developed over the past years with substantial success save for the problem of being domain specific and making it difficult to use the different systems across domains. This work attempts to surmount the problem by proposing the use of domain independent features with a maximum entropy model and a multiobjective genetic algorithm (MOGA) to select the best features. The methods used in this work are backed up by experiments of which the classifications are evaluated using two diverse domains. Conclusions are finally drawn and the outlook for future work is considered.