Query-Driven Strategy for On-the-Fly Term Spotting in Spontaneous Speech

Abstract : Spoken utterance retrieval was largely studied in the last decades, with the purpose of indexing large audio databases or of detecting keywords in continuous speech streams. While the indexing of closed corpora can be performed via a batch process, on-line spotting systems have to synchronously detect the targeted spoken utterances. We propose a two-level architecture for on-the-fly term spotting. The first level performs a fast detection of the speech segments that probably contain the targeted utterance. The second level refines the detection on the selected segments, by using a speech recognizer based on a query-driven decoding algorithm. Experiments are conducted on both broadcast and spontaneous speech corpora. We investigate the impact of the spontaneity level on system performance. Results show that our method remains effective even if the recognition rates are significantly degraded by disfluencies.
Document type :
Journal articles
Complete list of metadatas

Cited literature [32 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01320220
Contributor : Bibliothèque Universitaire Déposants Hal-Avignon <>
Submitted on : Thursday, November 9, 2017 - 1:30:30 PM
Last modification on : Saturday, March 23, 2019 - 1:22:34 AM
Long-term archiving on : Saturday, February 10, 2018 - 2:40:05 PM

File

10.1.1.604.1657.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Mickael Rouvier, Georges Linarès, Benjamin Lecouteux. Query-Driven Strategy for On-the-Fly Term Spotting in Spontaneous Speech. EURASIP Journal on Audio, Speech, and Music Processing, SpringerOpen, 2010, ⟨10.1155/2010/326578⟩. ⟨hal-01320220⟩

Share

Metrics

Record views

113

Files downloads

93