Demo Data from SIGIR 2026 / reviewers in the wild / expert
Ryoji Hamabe
dblp:71/6888
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Information extraction and text analysis
syntactic parsing |
0.1 | 1 | 2006 | 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 |
0.0 | 1 | 2006 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 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 |
ACL | 1 |
| 2006 | Detection of quotations and inserted clauses and its application to dependency structure analysis in spontaneous JapaneseabstractJapanese 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 |
INTERSPEECH | 1 |
| 2006 | Dependency-structure Annotation to Corpus of Spontaneous Japanese
Kiyotaka Uchimoto, Ryoji Hamabe, Takehiko Maruyama, Katsuya Takanashi, Tatsuya Kawahara, Hitoshi Isahara |
LREC | 2 |