Experiences in evaluating multilingual and text-image information retrieval

23 pages, 8 figures.One important step during the development of information retrieval (IR) processes is the evaluation of the output regarding the information needs of the user. The "high quality" of the output is related to the integration of different methods to be applied in the IR process and the information included in the retrieved documents, but how can "quality" be measured? Although some of these methods can be tested in a stand-alone way, it is not always clear what will happen when several methods are integrated. For this reason, much effort has been put into establishing a good combination of several methods or to correctly tuning some of the algorithms involved. The current approach is to measure the precision and recall figures yielded when different combinations of methods are included in an IR process. In this article, a short description of the current techniques and methods included in an IR system is given, paying special attention to the multilingual aspect of the problem. Also a discussion of their influence on the final performance of the IR process is presented by explaining previous experiences in the evaluation process followed in two projects (MIRACLE and OmniPaper) related to multilingual information retrieval.This work has been partially supported by the projects OmniPaper (European Union, 5th Framework Programme for Research and Technological Development, IST-2001-32174), NEDINE (E-Content project Ref.: 22225), and GPS Project—Software Process Management Platform: modeling, reuse, and measurement (National Research Plan, TIN2004-07083).Publicad

User experiments with the Eurovision cross-language image retrieval system

In this paper we present Eurovision, a text-based system for cross-language (CL) image retrieval. The system is evaluated by multilingual users for two search tasks with the system configured in English and five other languages. To our knowledge this is the first published set of user experiments for CL image retrieval. We show that: (1) it is possible to create a usable multilingual search engine using little knowledge of any language other than English, (2) categorizing images assists the user's search, and (3) there are differences in the way users search between the proposed search tasks. Based on the two search tasks and user feedback, we describe important aspects of any CL image retrieval system

An Investigation on Text-Based Cross-Language Picture Retrieval Effectiveness through the Analysis of User Queries

Purpose: This paper describes a study of the queries generated from a user experiment for cross-language information retrieval (CLIR) from a historic image archive. Italian speaking users generated 618 queries for a set of known-item search tasks. The queries generated by user’s interaction with the system have been analysed and the results used to suggest recommendations for the future development of cross-language retrieval systems for digital image libraries. Methodology: A controlled lab-based user study was carried out using a prototype Italian-English image retrieval system. Participants were asked to carry out searches for 16 images provided to them, a known-item search task. User’s interactions with the system were recorded and queries were analysed manually quantitatively and qualitatively. Findings: Results highlight the diversity in requests for similar visual content and the weaknesses of Machine Translation for query translation. Through the manual translation of queries we show the benefits of using high-quality translation resources. The results show the individual characteristics of user’s whilst performing known-item searches and the overlap obtained between query terms and structured image captions, highlighting the use of user’s search terms for objects within the foreground of an image. Limitations and Implications: This research looks in-depth into one case of interaction and one image repository. Despite this limitation, the discussed results are likely to be valid across other languages and image repository. Value: The growing quantity of digital visual material in digital libraries offers the potential to apply techniques from CLIR to provide cross-language information access services. However, to develop effective systems requires studying user’s search behaviours, particularly in digital image libraries. The value of this paper is in the provision of empirical evidence to support recommendations for effective cross-language image retrieval system design.</p

Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop

We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding the discovery of linguistic units (subwords and words) in a language without orthography. We study the replacement of orthographic transcriptions by images and/or translated text in a well-resourced language to help unsupervised discovery from raw speech.Comment: Accepted to ICASSP 201

Creating a test collection to evaluate diversity in image retrieval

This paper describes the adaptation of an existing test collection for image retrieval to enable diversity in the results set to be measured. Previous research has shown that a more diverse set of results often satisfies the needs of more users better than standard document rankings. To enable diversity to be quantified, it is necessary to classify images relevant to a given theme to one or more sub-topics or clusters. We describe the challenges in building (as far as we are aware) the first test collection for evaluating diversity in image retrieval. This includes selecting appropriate topics, creating sub-topics, and quantifying the overall effectiveness of a retrieval system. A total of 39 topics were augmented for cluster-based relevance and we also provide an initial analysis of assessor agreement for grouping relevant images into sub-topics or clusters

Evaluating performance of biomedical image retrieval systems - an overview of the medical image retrieval task at ImageCLEF 2004-2013

Medical image retrieval and classification have been extremely active research topics over the past 15 years. Within the ImageCLEF benchmark in medical image retrieval and classification, a standard test bed was created that allows researchers to compare their approaches and ideas on increasingly large and varied data sets including generated ground truth. This article describes the lessons learned in ten evaluation campaigns. A detailed analysis of the data also highlights the value of the resources created

Predicting language learners' grades in the L1, L2, L3 and L4: the effect of some psychological and sociocognitive variables

This study of 89 Flemish high-school students' grades for L1 (Dutch), L2 (French), L3 (English) and L4 (German) investigates the effects of three higher-level personality dimensions (psychoticism, extraversion, neuroticism), one lower-level personality dimension (foreign language anxiety) and sociobiographical variables (gender, social class) on the participants' language grades. Analyses of variance revealed no significant effects of the higher-level personality dimensions on grades. Participants with high levels of foreign language anxiety obtained significantly lower grades in the L2 and L3. Gender and social class had no effect. Strong positive correlations between grades in the different languages could point to an underlying sociocognitive dimension. The implications of these findings are discussed