Title
Vapor Engine: Demonstrating an Early Prototype of a Language-Independent Search Engine for Speech.
Abstract
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.
Year
DOI
Venue
2016
10.1145/2854946.2854987
CHIIR
Field
DocType
ISBN
Transcription (linguistics),Speech retrieval,Search engine,Information retrieval,Ranking,Computer science,Word recognition,Search engine indexing,Preprocessor,Artificial intelligence,Natural language processing,Audio signal processing
Conference
978-1-4503-3751-9
Citations 
PageRank 
References 
1
0.40
13
Authors
4
Name
Order
Citations
PageRank
Douglas W. Oard12484246.11
Rashmi Sankepally2113.46
Jerome White3396.99
Craig Harman418511.41