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Ryoji Hamabe

dblp:71/6888 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2006
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Information extraction and text analysis · 87% Speech recognition and synthesis · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis
syntactic parsing
0.112006
Detection of Quotations and Inserted Clauses and Its Application to Dependency Structure Analysis in Spontaneous Japanese · ACL 2006
Natural language and speech › Speech recognition and synthesis
spontaneous speech processing
0.012006
Detection of Quotations and Inserted Clauses and Its Application to Dependency Structure Analysis in Spontaneous Japanese · ACL 2006

Methods — techniques the papers use, named apart from their topics

dependency parsing · 0.1
YearPublicationVenuePosition
2006 Detection of Quotations and Inserted Clauses and Its Application to Dependency Structure Analysis in Spontaneous Japanese
Ryoji Hamabe, Kiyotaka Uchimoto, Tatsuya Kawahara, Hitoshi Isahara
ACL1
2006 Detection of quotations and inserted clauses and its application to dependency structure analysis in spontaneous Japanese
abstract
Japanese dependency structure is usually represented by relationships between phrasal units called bunsetsus. One of the biggest problems with dependency structure analysis in spontaneous speech is that clause boundaries are ambiguous. This paper describes a method for detecting the boundaries of quotations and inserted clauses and that for improving the dependency accuracy by applying the detected boundaries to dependency structure analysis. The quotations and inserted clauses are determined by using an SVM-based text chunking method that considers information on morphemes, pauses, fillers, etc. The information on automatically analyzed dependency structure is also used to detect the beginning of the clauses. Our evaluation experiment using Corpus of Spontaneous Japanese (CSJ) showed that the automatically estimated boundaries of quotations and inserted clauses helped to improve the accuracy of dependency structure analysis.
Ryoji Hamabe, Kiyotaka Uchimoto, Tatsuya Kawahara, Hitoshi Isahara
INTERSPEECH1
2006 Dependency-structure Annotation to Corpus of Spontaneous Japanese
Kiyotaka Uchimoto, Ryoji Hamabe, Takehiko Maruyama, Katsuya Takanashi, Tatsuya Kawahara, Hitoshi Isahara
LREC2