Syntactic Filtering and Content-Based Retrieval of Twitter Sentences for the Generation of System Utterances in Dialogue Systems
| Autor: | Hirano Toru, Toshiro Makino, Ryuichiro Higashinaka, Matsuo Yoshihiro, Toyomi Meguro, Kobayashi Nozomi, Miyazaki Chiaki |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Response generation
Structure (mathematical logic) Computer science business.industry Speech recognition computer.software_genre Noun phrase Resource (project management) Noise (video) Artificial intelligence business computer Relevant information Natural language processing Sentence Content based retrieval |
| Zdroj: | Signals and Communication Technology ISBN: 9783319218335 IWSDS |
| DOI: | 10.1007/978-3-319-21834-2_2 |
| Popis: | Sentences extracted from Twitter have been seen as a valuable resource for response generation in dialogue systems. However, selecting appropriate ones is difficult due to their noise. This paper proposes tackling such noise by syntactic filtering and content-based retrieval. Syntactic filtering ascertains the valid sentence structure as system utterances, and content-based retrieval ascertains that the content has the relevant information related to user utterances. Experimental results show that our proposed method can appropriately select high-quality Twitter sentences, significantly outperforming the baseline. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|