A system for spoken query information retrieval on mobile devices
| Autor: | Yu Shi, Eric Chang, Zhuoran Chen, Yuk-Chi Li, Frank Seide, Helen Meng |
|---|---|
| Rok vydání: | 2002 |
| Předmět: |
Information retrieval
Acoustics and Ultrasonics business.industry Computer science InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Information access Query expansion Human–computer information retrieval NIST Mobile search Relevance (information retrieval) Computer Vision and Pattern Recognition Mobile telephony Electrical and Electronic Engineering business Mobile device Software |
| Zdroj: | IEEE Transactions on Speech and Audio Processing. 10:531-541 |
| ISSN: | 1063-6676 |
| DOI: | 10.1109/tsa.2002.804301 |
| Popis: | With the proliferation of handheld devices, information access on mobile devices is a topic of growing relevance. This paper presents a system that allows the user to search for information on mobile devices using spoken natural-language queries. We explore several issues related to the creation of this system, which combines state-of-the-art speech-recognition and information-retrieval technologies. This is the first work that we are aware of which evaluates spoken query based information retrieval on a commonly available and well researched text database, the Chinese news corpus used in the National Institute of Standards and Technology (NIST)s TREC-5 and TREC-6 benchmarks. To compare spoken-query retrieval performance for different relevant scenarios and recognition accuracies, the benchmark queries-read verbatim by 20 speakers-were recorded simultaneously through three channels: headset microphone, PDA microphone, and cellular phone. Our results show that for mobile devices with high-quality microphones, spoken-query retrieval based on existing technologies yields retrieval precisions that come close to that for perfect text input (mean average precision 0.459 and 0.489, respectively, on TREC-6). |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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