Vapor Engine
Autor: | Craig Harman, Rashmi Sankepally, Douglas W. Oard, Jerome White |
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Rok vydání: | 2016 |
Předmět: |
Information retrieval
Repetition (rhetorical device) Computer science business.industry Interface (Java) Search engine indexing 02 engineering and technology computer.software_genre Term (time) 030507 speech-language pathology & audiology 03 medical and health sciences Search engine 020204 information systems Word recognition 0202 electrical engineering electronic engineering information engineering Preprocessor Artificial intelligence 0305 other medical science business Audio signal processing computer Natural language processing |
Zdroj: | CHIIR |
DOI: | 10.1145/2854946.2854987 |
Popis: | Typical search engines for spoken content begin with some form of language-specific audio processing such as phonetic word recognition. Many languages, however, lack the language tuned preprocessing tools that are needed to create indexing terms for speech. One approach in such cases is to rely on repetition, detected using acoustic features, to find terms that might be worth indexing. Experiments have shown that this approach yields term sets that might be sufficient for some applications in both spoken term detection and ranked retrieval experiments. Such approaches currently work only with spoken queries, however, and only when the searcher is able to speak in a manner similar to that of the speakers in the collection. This demonstration paper proposes Vapor Engine, a new tool for selectively transcribing repeated terms that can be automatically detected from spoken content in any language. These transcribed terms could then be matched to queries formulated using written terms. Vapor Engine is early in development: it currently supports only single-term queries and has not yet having been formally evaluated. This paper introduces the interface and summarizes the challenges it seeks to address. |
Databáze: | OpenAIRE |
Externí odkaz: |
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