24553
Mandarin-English Information (MEI): investigating translingual speech retrieval
Abstract This paper describes the Mandarin–English Information (MEI) project, where we investigated the problem of cross-language spoken document retrieval (CL-SDR), and developed one of the first English–Chinese CL-SDR systems. Our system accepts an entire English news story (text) as query, and retrieves relevant Chinese broadcast news stories (audio) from the document collection. Hence, this is a cross-language and cross-media retrieval task. We applied a multi-scale approach to our problem, which unifies the use of phrases, words and subwords in retrieval. The English queries are translated into Chinese by means of a dictionary-based approach, where we have integrated phrase-based translation with word-by-word translation. Untranslatable named entities are transliterated by a novel subword translation technique. The multi-scale approach can be divided into three subtasks – multi-scale query formulation, multi-scale audio indexing (by speech recognition) and multi-scale retrieval. Experimental results demonstrate that the use of phrase-based translation and subword translation gave performance gains, and multi-scale retrieval outperforms word-based retrieval.
12859800
Building an information retrieval test collection for spontaneous conversational speech
Test collections model use cases in ways that facilitate evaluation of information retrieval systems. This paper describes the use of search-guided relevance assessment to create a test collection for retrieval of spontaneous conversational speech. Approximately 10,000 thematically coherent segments were manually identified in 625 hours of oral history interviews with 246 individuals. Automatic speech recognition results, manually prepared summaries, controlled vocabulary indexing, and name authority control are available for every segment. Those features were leveraged by a team of four relevance assessors to identify topically relevant segments for 28 topics developed from actual user requests. Search-guided assessment yielded sufficient inter-annotator agreement to support formative evaluation during system development. Baseline results for ranked retrieval are presented to illustrate use of the collection.
22535159
Interactive Cross-Language Document Selection
The problem of finding documents written in a language that the searcher cannot read is perhaps the most challenging application of cross-language information retrieval technology. In interactive applications, that task involves at least two steps: (1) the machine locates promising documents in a collection that is larger than the searcher could scan, and (2) the searcher recognizes documents relevant to their intended use from among those nominated by the machine. This article presents the results of experiments designed to explore three techniques for supporting interactive relevance assessment: (1) full machine translation, (2) rapid term-by-term translation, and (3) focused phrase translation. Machine translation was found to better support this task than term-by-term translation, and focused phrase translation further improved recall without an adverse effect on precision. The article concludes with an assessment of the strengths and weaknesses of the evaluation framework used in this study and some remarks on implications of these results for future evaluation campaigns.
14844222
Summarization Design for Interactive Cross-Language Question Answering
This paper describes an experimental investigation of interactive techniques for cross-language information access. The task was to answer factual questions from a large collection of documents written in a language in which the user has little proficiency. An interactive cross-language retrieval system that included optional user-assisted query translation, display of translated summaries for individual document ranked in order of decreasing degree of match to the user's query, and optional full-text examination of individual documents was provided. Two alternative types of extractive summaries were tried using a systematically varied presentation order, one drawn from a single segment of the translated document and the other drawn from three (usually) shorter segments of the translated document. On average, users were able to correctly answer just 62% of the sixteen assigned questions in an average of 176 seconds per question. Little difference was found between the two summary types for this task in an experiment using eight human subjects. Time on task and the number of query iterations were found to exhibit a positive correlation with question difficulty.
13917172
iCLEF 2003 at Maryland: Translation Selection and Document Selection
Maryland performed two sets of experiments for the 2003 Cross-Language Evaluation Forum’s interactive track, one focused on interactive selection of appropriate translations for query terms, the second focused on interactive selection of relevant documents. Translation selection was supported using possible synonyms discovered through back translation and two techniques for generating KeyWord In Context (KWIC) examples of usage. The results indicate that searchers typically achieved a similar search effectiveness using fewer query iterations when interactive translation selection was available. For document selection, a complete extract of the first 40 words of each news story was compared to a compressed extract generated using an automated parse-and-trim approach that approximates one way in which people can produce headlines. The results indicate that compressed “headlines” result in faster assessment, but with a 20% relative reduction in the F α= 0.8 search effectiveness measure.
5646579
Comparing User-assisted and Automatic Query Translation
For the 2002 Cross-Language Evaluation Forum Interactive Track, the University of Maryland team focused on query formulation and reformulation. Twelve people performed a total of forty eight searches in the German document collection using English queries. Half of the searches were with user-assisted query translation, and half with fully automatic query translation. For the user-assisted query translation condition, participants were provided two types of cues about the meaning of each translation: a list of other terms with the same translation (potential synonyms), and a sentence in which the word was used in a translation-appropriate context. Four searchers performed the official iCLEF task, the other eight searched a smaller collection. Searchers performing the official task were able to make more accurate relevance judgments with user-assisted query translation for three of the four topics. We observed that the number of query iterations seems to vary systematically with topic, system, and collection, and we are analyzing query content and ranked retrieval measures to obtain further insight into these variations in search behavior.
15835310
An Intuitive Formal Approach to Dynamic Workflow Modeling and Analysis
The increasing dynamics and the continuous changes of business processes raise a challenge to the research and implementation of workflows. The significance of applying formal approaches to the modeling and analysis of workflows has been well recognized and many such approaches have been proposed. However, these approaches require users to master considerable knowledge of the particular formalisms, which impacts the application of these approaches on a larger scale. This paper presents a new formal, yet intuitive approach for the modeling and analysis of workflows, which attempts to overcome the above problem. In addition to the abilities of supporting workflow validation and enactment, this new approach possesses the distinguishing feature of allowing users who are not proficient in formal methods to build up and dynamically modify the workflow models that address their business needs.
13018290
Towards Web Mining of Query Translations for Cross-Language Information Retrieval in Digital Libraries
This paper proposes an efficient client-server-based query translation approach to allowing more feasible implementation of cross-language information retrieval (CLIR) services in digital library (DL) systems. A centralized query translation server is constructed to process the translation requests of cross-lingual queries from connected DL systems. To extract translations not covered by standard dictionaries, the server is developed based on a novel integration of dictionary resources and Web mining methods, including anchor-text and search-result methods, which exploit huge amounts of multilingual and wide-scoped Web resources as live bilingual corpora to alleviate translation difficulties, and have been proven particularly effective for extracting multilingual translation equivalents of query terms containing proper names or new terminologies. The proposed approach was implemented in a query translation engine called LiveTrans, which has been shown its feasibility in providing efficient English-Chinese CLIR services for DL.
11677932
Fast Similarity Search in Three-Dimensional Structure Databases
Given a database D of three-dimensional (3D) molecular structures and a target molecule Q, the similarity search problem is to find the molecules O in D that match Q after allowing for an arbitrary number of whole-structure rotations and translations as well as a certain number of edit operations. The edit operations include relabeling an atom, deleting an atom, and inserting an atom. This search operation arises in many biochemical applications. In this paper we study the similarity search problem and a class of related queries. We present a computer vision based technique, called geometric hashing, for processing these queries. Experimental results on a database of 3D molecular structures obtained from the National Cancer Institute indicate the good performance of the presented technique.
11945508
Content-Based Audio Classification Using Support Vector Machines and Independent Component Analysis
In this paper, we present a new audio classification system. First, a frame-based multiclass support vector machine (SVM) for audio classification is proposed. The accuracy rate has significant improvements over conventional file-based SVM audio classifier. In feature selection, this study transforms the log powers of the critical-band filters based on independent component analysis (ICA). This new audio feature is combined with mel-frequency cepstral coefficients (MFCCs) and five perceptual features to form an audio feature set. The superiority of the proposed system has been demonstrated via a 15-class sound database with a 91.7% accuracy rate
94229
Translating unknown queries with web corpora for cross-language information retrieval
It is crucial for cross-language information retrieval (CLIR) systems to deal with the translation of unknown queries due to that real queries might be short. The purpose of this paper is to investigate the feasibility of exploiting the Web as the corpus source to translate unknown queries for CLIR. We propose an online translation approach to determine effective translations for unknown query terms via mining of bilingual search-result pages obtained from Web search engines. This approach can alleviate the problem of the lack of large bilingual corpora, translate many unknown query terms, provide flexible query specifications, and extract semantically-close translations to benefit CLIR tasks -- especially for cross-language Web search.