We introduce pre-post-editing, possibly the most basic form of interactive translation, as a touch-based interaction with iteratively improved translation hypotheses prior to classical post-editing.We report simulated experiments that yield very large improvements on classical evaluation metrics (up to 21 BLEU) as well as on a parameterized variant of the TER metric that takes into account the cost of matching/touching tokens, confirming the promising prospects of the novel translation scenarios offered by our approach.

Numerous works in Statistical Machine Translation (SMT) have attempted to iden-tify better translation hypotheses obtained by an initial decoding using an improved, but more costly scoring function. In this work, we introduce an approach that takes the hypotheses produced by a state-of-the-art, reranked phrase-based SMT sys-tem, and explores new parts of the search space by applying rewriting rules se-lected on the basis of posterior phrase-level confidence. In the medical do-main, we obtain a 1.9 BLEU improve-ment over a reranked baseline exploiting the same scoring function, corresponding to a 5.4 BLEU improvement over the orig-inal Moses baseline. We show that if an indication of which phrases require rewrit-ing is provided, our automatic rewriting procedure yields an additional improve-ment of 1.5 BLEU. Various analyses, in-cluding a manual error analysis, further il-lustrate the good performance and poten-tial for improvement of our approach in spite of its simplicity. 1

This work uses parallel monolingual corpora for a detailed study of the task of sub-sentential paraphrase acquisition. We argue that the scarcity of this type of resource is compensated by the fact that it is the most suited type for studies on paraphrasing. We propose a large exploration of this task with experiments on two languages with five different acquisition techniques, selected for their complementarity, their combinations, as well as four monolingual corpus types of varying comparability. We report, under all conditions, a significant improvement over all techniques by validating candidate paraphrases using a maximum entropy classifier. An important result of our study is the identification of difficult-to-acquire paraphrase pairs, which are classified and quantified in a bilingual typology.

Abstract One of the basic topics of question answering (QA) dialogue systems is how follow-up questions should be interpreted by a QA system. In this paper, we shall discuss our experience with the IMIX and Ritel systems, for both of which a follow-up question handling scheme has been developed, and corpora have been collected. These two systems are each other's opposites in many respects: IMIX is multimodal, non-factoid, black-box QA, while Ritel is speech, factoid, keyword-based QA. Nevertheless, we will show that they are quite comparable, and that it is fruitful to examine the similarities and differences. We shall look at how the systems are composed, and how real, non-expert, users interact with the systems. We shall also provide comparisons with systems from the literature where possible, and indicate where open issues lie and in what areas existing systems may be improved. We conclude that most systems have a common architecture with a set of common subtasks, in particular detecting follow-up questions and finding referents for them. We characterise these tasks using the typical techniques used for performing them, and data from our corpora. We also identify a special type of follow-up question, the discourse question, which is asked when the user is trying to understand an answer, and propose some basic methods for handling it.

The Ritel system aims to provide open-domain question answering to casual users by means of a telephone dialogue. This implies some unique challenges, such as very fast overall performance and large-vocabulary speech recognition. Speech QA is an error-prone process, but errors or problems that occur may be resolved with help of user feedback, as part of a natural dialogue. This paper reports on a pilot study conducted with the latest version of Ritel, which includes search term confirmation and improved follow-up question handling, as well as various improvements on the other system components. We collected a small dialogue corpus with the new system, which we use to evaluate and discuss it. Index Terms: speech QA, dialogue systems, confirmation. 1. The Ritel platform

The Ritel project aims at integrating spoken language dialog and open-domain information retrieval to allow a human to ask general questions (e.g. Who is currently presiding the French Senate?) and refine her search interactively. This project is at the junction of several distinct research communities, and has therefore several challenges to tackle: real-time streamed speech recognition with very large vocabulary, open-domain dialog management, fast information retrieval from text, query cobuilding, communication between information retrieval and dialog components, and generation of natural sounding answers. In this paper, we present our work on the different components of Ritel, and provide initial results.