Portability of a spoken dialogue system (SDS) to a new domain or a new language is a hot topic as it may imply gains in time and cost for building new SDSs. In particular in this paper we investigate several fast and efficient approaches for language portability of the spoken language understanding (SLU) module of a dialogue system. We show that the use of statistical machine translation (SMT) can reduce the time and the cost of porting a system from a source to a target language. For conceptual decoding, a state-of-the-art module based on conditional random fields (CRF) is used and a new approach based on phrase-based statistical machine translation (PB-SMT) is also evaluated. The experimental results show the efficiency of the proposed methods for a fast and low cost SLU language portability. In addition, we propose two methods to increase SLU robustness to translation errors. Overall, it is shown that the combination of all these approaches can further reduce the concept error rate. While most of the experiments in this paper deal with portability from French to Italian (given the availability of the Media French corpus and its subset manually translated into Italian), a validation of our methodology is eventually proposed in Arabic.

Comparison and Combination of Lightly Supervised Approaches for Language Portability of a Spoken Language Understanding System

When humans give route directions, they use gestures to indicate the location of landmarks. The form of these gestures reflects that speakers take one of several perspectives when producing them. They may locate the landmark with respect to the speaker, with respect to the person following the route, or with respect to other landmarks. A corpus study shows that which perspective is chosen is partly determined by the function of the discourse segment these gestures occur in. Since locating gestures are so prevalent in direction-giving, in this paper we address the kinds of dialogue information and knowledge representation that is needed to generate them automatically.

/pdf/knowledge-representation-for-generating-locating-gestures-in-4efixkqedq.pdf

Knowledge Representation for Generating Locating Gestures in Route Directions

While Online Publishing has replaced most traditional printed journals in less than twenty years, today’s Online Publication Formats are still closely bound to the medium of paper. Collaboration is mostly hidden from the readership, and ‘final’ versions of papers are stored in ‘publisher PDF’ files mimicking print. Meanwhile new media formats originating from the web itself bring us new modes of transparent collaboration, feedback, continued refinement, and reusability of (scholarly) works: Wikis, Blogs and Code Repositories, to name a few. This chapter characterizes the potentials of Dynamic Publication Formats and analyzes necessary prerequisites. Selected tools specific to the aims, stages, and functions of Scholarly Publishing are presented. Furthermore, this chapter points out early examples of usage and further development from the field. In doing so, Dynamic Publication Formats are described as (a) a ‘parallel universe’ based on the commodification of (scholarly) media, and (b) as a much needed complement, slowly recognized and incrementally integrated into more efficient and dynamic workflows of production, improvement, and dissemination of scholarly knowledge in general.

/pdf/dynamic-publication-formats-and-collaborative-authoring-17x6k0zvyo.pdf

Dynamic Publication Formats and Collaborative Authoring

In this paper, we propose a method to identify good quality Wikipedia articles by mutually evaluating editors and texts. A major approach for assessing article quality is a text survival ratio based approach. In this approach, when a text survives beyond multiple edits, the text is assessed as good quality. This approach assumes that poor quality texts are deleted by editors with high possibility. However, many vandals delete good quality texts frequently, then the survival ratios of good quality texts are improperly decreased by vandals. As a result, many good quality texts are unfairly assessed as poor quality. In our method, we consider editor quality for calculating text quality, and decrease the impacts on text qualities by the vandals who has low quality. Using this improvement, the accuracy of the text quality should be improved. However, an inherent problem of this idea is that the editor qualities are calculated by the text qualities. To solve this problem, we mutually calculate the editor and text qualities until they converge. We did our experimental evaluation, and we confirmed that the proposed method could accurately assess the text qualities.

Mutual evaluation of editors and texts for assessing quality of Wikipedia articles

In this paper, we propose a method for assessing quality values of Wikipedia articles from edit history using h-index. One of the major methods for assessing Wikipedia article quality is a peer-review based method. In this method, we assume that if an editor’s texts are left by the other editors, the texts are approved by the editors, then the editor is decided as a good editor. However, if an editor edits multiple articles, and the editor is approved at a small number of articles, the quality value of the editor deeply depends on the quality of the texts. In this paper, we apply h-index, which is a simple but resistant to excessive values, to the peer-review based Wikipedia article assessment method. Although h-index can identify whether an editor is a good quality editor or not, h-index cannot identify whether the editor is a vandal or an inactive editor. To solve this problem, we propose p-ratio for identifying which editors are vandals or inactive editors. From our experiments, we confirmed that by integrating h-index with p-ratio, the accuracy of article quality assessment in our method outperforms the existing peer-review based method.

Quality Assessment of Wikipedia Articles Using h-index

We review existing types of dialogue managers (DMs), and propose that the Information State (IS) approach may allow both complexity of dialogue and ease of portability. We discuss implementational drawbacks of the only existing IS DM, and describe our work underway to develop a new DM resolving those drawbacks.

Dialogue complexity with portability?: research directions for the information state approach

Wiki users receive very little guidance on the trustworthiness of the information they find. It is difficult for them to determine how long the text in a page has existed, or who originally authored the text. It is also difficult to assess the reliability of authors contributing to a wiki page. In this paper, we create a set of trust indicators and metrics derived from phrasal analysis of the article revision history. These metrics include author attribution, author reputation, expertise ratings, article evolution, and text trustworthiness. We also propose a new technique for collecting and maintaining explicit article ratings across multiple revisions.

Wiki trust metrics based on phrasal analysis

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Dialogue complexity with portability?: research directions for the information state approach

Wiki trust metrics based on phrasal analysis