Models, code, and papers for "Tetsuya Ishikawa":

Summarizing Encyclopedic Term Descriptions on the Web

Jul 10, 2004
Atsushi Fujii, Tetsuya Ishikawa

We are developing an automatic method to compile an encyclopedic corpus from the Web. In our previous work, paragraph-style descriptions for a term are extracted from Web pages and organized based on domains. However, these descriptions are independent and do not comprise a condensed text as in hand-crafted encyclopedias. To resolve this problem, we propose a summarization method, which produces a single text from multiple descriptions. The resultant summary concisely describes a term from different viewpoints. We also show the effectiveness of our method by means of experiments.

* Proceedings of the 20th International Conference on Computational Linguistics (COLING 2004), pp.645-651, Aug. 2004 
* 7 pages, Proceedings of the 20th International Conference on Computational Linguistics (to appear) 

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Japanese/English Cross-Language Information Retrieval: Exploration of Query Translation and Transliteration

Jun 09, 2002
Atsushi Fujii, Tetsuya Ishikawa

Cross-language information retrieval (CLIR), where queries and documents are in different languages, has of late become one of the major topics within the information retrieval community. This paper proposes a Japanese/English CLIR system, where we combine a query translation and retrieval modules. We currently target the retrieval of technical documents, and therefore the performance of our system is highly dependent on the quality of the translation of technical terms. However, the technical term translation is still problematic in that technical terms are often compound words, and thus new terms are progressively created by combining existing base words. In addition, Japanese often represents loanwords based on its special phonogram. Consequently, existing dictionaries find it difficult to achieve sufficient coverage. To counter the first problem, we produce a Japanese/English dictionary for base words, and translate compound words on a word-by-word basis. We also use a probabilistic method to resolve translation ambiguity. For the second problem, we use a transliteration method, which corresponds words unlisted in the base word dictionary to their phonetic equivalents in the target language. We evaluate our system using a test collection for CLIR, and show that both the compound word translation and transliteration methods improve the system performance.

* Computers and the Humanities, Vol.35, No.4, pp.389-420, 2001 

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Organizing Encyclopedic Knowledge based on the Web and its Application to Question Answering

Jun 10, 2001
Atsushi Fujii, Tetsuya Ishikawa

We propose a method to generate large-scale encyclopedic knowledge, which is valuable for much NLP research, based on the Web. We first search the Web for pages containing a term in question. Then we use linguistic patterns and HTML structures to extract text fragments describing the term. Finally, we organize extracted term descriptions based on word senses and domains. In addition, we apply an automatically generated encyclopedia to a question answering system targeting the Japanese Information-Technology Engineers Examination.

* Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics (ACL-EACL 2001), pp.196-203, July. 2001 
* 8 pages, Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics (To appear) 

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Applying Machine Translation to Two-Stage Cross-Language Information Retrieval

Nov 02, 2000
Atsushi Fujii, Tetsuya Ishikawa

Cross-language information retrieval (CLIR), where queries and documents are in different languages, needs a translation of queries and/or documents, so as to standardize both of them into a common representation. For this purpose, the use of machine translation is an effective approach. However, computational cost is prohibitive in translating large-scale document collections. To resolve this problem, we propose a two-stage CLIR method. First, we translate a given query into the document language, and retrieve a limited number of foreign documents. Second, we machine translate only those documents into the user language, and re-rank them based on the translation result. We also show the effectiveness of our method by way of experiments using Japanese queries and English technical documents.

* Proceedings of the 4th Conference of the Association for Machine Translation in the Americas (AMTA-2000), pp.13-24, Oct. 2000 
* 13 pages, 1 Postscript figure 

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A Novelty-based Evaluation Method for Information Retrieval

Nov 02, 2000
Atsushi Fujii, Tetsuya Ishikawa

In information retrieval research, precision and recall have long been used to evaluate IR systems. However, given that a number of retrieval systems resembling one another are already available to the public, it is valuable to retrieve novel relevant documents, i.e., documents that cannot be retrieved by those existing systems. In view of this problem, we propose an evaluation method that favors systems retrieving as many novel documents as possible. We also used our method to evaluate systems that participated in the IREX workshop.

* Proceedings of the 2nd International Conference on Language Resources and Evaluation (LREC-2000), pp.1637-1641, Jun. 2000 
* 5 pages 

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Utilizing the World Wide Web as an Encyclopedia: Extracting Term Descriptions from Semi-Structured Texts

Nov 02, 2000
Atsushi Fujii, Tetsuya Ishikawa

In this paper, we propose a method to extract descriptions of technical terms from Web pages in order to utilize the World Wide Web as an encyclopedia. We use linguistic patterns and HTML text structures to extract text fragments containing term descriptions. We also use a language model to discard extraneous descriptions, and a clustering method to summarize resultant descriptions. We show the effectiveness of our method by way of experiments.

* Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics (ACL-2000), pp.488-495, Oct. 2000 
* 8 pages, 2 Postscript figures 

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Cross-Language Information Retrieval for Technical Documents

Jul 07, 1999
Atsushi Fujii, Tetsuya Ishikawa

This paper proposes a Japanese/English cross-language information retrieval (CLIR) system targeting technical documents. Our system first translates a given query containing technical terms into the target language, and then retrieves documents relevant to the translated query. The translation of technical terms is still problematic in that technical terms are often compound words, and thus new terms can be progressively created simply by combining existing base words. In addition, Japanese often represents loanwords based on its phonogram. Consequently, existing dictionaries find it difficult to achieve sufficient coverage. To counter the first problem, we use a compound word translation method, which uses a bilingual dictionary for base words and collocational statistics to resolve translation ambiguity. For the second problem, we propose a transliteration method, which identifies phonetic equivalents in the target language. We also show the effectiveness of our system using a test collection for CLIR.

* Proceedings of the Joint ACL SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, pp.29-37, 1999 
* 9 pages, 5 Postscript figures, uses colacl.sty and psfig.tex 

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Speech-Driven Text Retrieval: Using Target IR Collections for Statistical Language Model Adaptation in Speech Recognition

Jun 24, 2002
Atsushi Fujii, Katunobu Itou, Tetsuya Ishikawa

Speech recognition has of late become a practical technology for real world applications. Aiming at speech-driven text retrieval, which facilitates retrieving information with spoken queries, we propose a method to integrate speech recognition and retrieval methods. Since users speak contents related to a target collection, we adapt statistical language models used for speech recognition based on the target collection, so as to improve both the recognition and retrieval accuracy. Experiments using existing test collections combined with dictated queries showed the effectiveness of our method.

* Anni R. Coden and Eric W. Brown and Savitha Srinivasan (Eds.), Information Retrieval Techniques for Speech Applications (LNCS 2273), pp.94-104, Springer, 2002 

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Language Modeling for Multi-Domain Speech-Driven Text Retrieval

Jun 24, 2002
Katunobu Itou, Atsushi Fujii, Tetsuya Ishikawa

We report experimental results associated with speech-driven text retrieval, which facilitates retrieving information in multiple domains with spoken queries. Since users speak contents related to a target collection, we produce language models used for speech recognition based on the target collection, so as to improve both the recognition and retrieval accuracy. Experiments using existing test collections combined with dictated queries showed the effectiveness of our method.

* IEEE Automatic Speech Recognition and Understanding Workshop, Dec. 2001 

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A Probabilistic Method for Analyzing Japanese Anaphora Integrating Zero Pronoun Detection and Resolution

Jun 20, 2002
Kazuhiro Seki, Atsushi Fujii, Tetsuya Ishikawa

This paper proposes a method to analyze Japanese anaphora, in which zero pronouns (omitted obligatory cases) are used to refer to preceding entities (antecedents). Unlike the case of general coreference resolution, zero pronouns have to be detected prior to resolution because they are not expressed in discourse. Our method integrates two probability parameters to perform zero pronoun detection and resolution in a single framework. The first parameter quantifies the degree to which a given case is a zero pronoun. The second parameter quantifies the degree to which a given entity is the antecedent for a detected zero pronoun. To compute these parameters efficiently, we use corpora with/without annotations of anaphoric relations. We show the effectiveness of our method by way of experiments.

* Proceedings of the 19th International Conference on Computational Linguistics (COLING 2002), pp.911-917, Aug. 2002 
* Proceedings of the 19th International Conference on Computational Linguistics (To appear) 

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A Method for Open-Vocabulary Speech-Driven Text Retrieval

Jun 09, 2002
Atsushi Fujii, Katunobu Itou, Tetsuya Ishikawa

While recent retrieval techniques do not limit the number of index terms, out-of-vocabulary (OOV) words are crucial in speech recognition. Aiming at retrieving information with spoken queries, we fill the gap between speech recognition and text retrieval in terms of the vocabulary size. Given a spoken query, we generate a transcription and detect OOV words through speech recognition. We then correspond detected OOV words to terms indexed in a target collection to complete the transcription, and search the collection for documents relevant to the completed transcription. We show the effectiveness of our method by way of experiments.

* Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP-2002), pp.188-195, July. 2002 
* Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (To appear) 

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Unsupervised Topic Adaptation for Lecture Speech Retrieval

Jul 10, 2004
Atsushi Fujii, Katunobu Itou, Tomoyosi Akiba, Tetsuya Ishikawa

We are developing a cross-media information retrieval system, in which users can view specific segments of lecture videos by submitting text queries. To produce a text index, the audio track is extracted from a lecture video and a transcription is generated by automatic speech recognition. In this paper, to improve the quality of our retrieval system, we extensively investigate the effects of adapting acoustic and language models on speech recognition. We perform an MLLR-based method to adapt an acoustic model. To obtain a corpus for language model adaptation, we use the textbook for a target lecture to search a Web collection for the pages associated with the lecture topic. We show the effectiveness of our method by means of experiments.

* Proceedings of the 8th International Conference on Spoken Language Processing (ICSLP 2004), pp.2957-2960, Oct. 2004 
* 4 pages, Proceedings of the 8th International Conference on Spoken Language Processing (to appear) 

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A Cross-media Retrieval System for Lecture Videos

Sep 13, 2003
Atsushi Fujii, Katunobu Itou, Tomoyosi Akiba, Tetsuya Ishikawa

We propose a cross-media lecture-on-demand system, in which users can selectively view specific segments of lecture videos by submitting text queries. Users can easily formulate queries by using the textbook associated with a target lecture, even if they cannot come up with effective keywords. Our system extracts the audio track from a target lecture video, generates a transcription by large vocabulary continuous speech recognition, and produces a text index. Experimental results showed that by adapting speech recognition to the topic of the lecture, the recognition accuracy increased and the retrieval accuracy was comparable with that obtained by human transcription.

* Proceedings of the 8th European Conference on Speech Communication and Technology (Eurospeech 2003), pp.1149-1152, Sep. 2003 

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PRIME: A System for Multi-lingual Patent Retrieval

Jun 24, 2002
Shigeto Higuchi, Masatoshi Fukui, Atsushi Fujii, Tetsuya Ishikawa

Given the growing number of patents filed in multiple countries, users are interested in retrieving patents across languages. We propose a multi-lingual patent retrieval system, which translates a user query into the target language, searches a multilingual database for patents relevant to the query, and improves the browsing efficiency by way of machine translation and clustering. Our system also extracts new translations from patent families consisting of comparable patents, to enhance the translation dictionary.

* Proceedings of MT Summit VIII, pp.163-167, Sep. 2001 

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Applying a Hybrid Query Translation Method to Japanese/English Cross-Language Patent Retrieval

Jun 24, 2002
Masatoshi Fukui, Shigeto Higuchi, Youichi Nakatani, Masao Tanaka, Atsushi Fujii, Tetsuya Ishikawa

This paper applies an existing query translation method to cross-language patent retrieval. In our method, multiple dictionaries are used to derive all possible translations for an input query, and collocational statistics are used to resolve translation ambiguity. We used Japanese/English parallel patent abstracts to perform comparative experiments, where our method outperformed a simple dictionary-based query translation method, and achieved 76% of monolingual retrieval in terms of average precision.

* ACM SIGIR 2000 Workshop on Patent Retrieval, July, 2000 

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