logo Idiap Research Institute        
 [BibTeX] [Marc21]
IMPROVING ACOUSTIC BASED KEYWORD SPOTTING USING LVCSR LATTICES
Type of publication: Idiap-RR
Citation: Motlicek_Idiap-RR-36-2012
Number: Idiap-RR-36-2012
Year: 2012
Month: 12
Institution: Idiap
Address: Rue Marconi 19
Abstract: This paper investigates detection of English keywords in a conversational scenario using a combination of acoustic and LVCSR based keyword spotting systems. Acoustic KWS systems search predefined words in parameterized spoken data. Corresponding confidences are represented by likelihood ratios given the keyword models and a background model. First, due to the especially high number of false-alarms, the acoustic KWS system is augmented with confidence measures estimated from corresponding LVCSR lattices. Then, various strategies to combine scores estimated by the acoustic and several LVCSR based KWS systems are explored. We show that a linear regression based combination significantly outperforms other (model-based) techniques. Due to that, the relative number of false-alarms of the combined KWS system decreased by more than 50% compared to the acoustic KWS system. Finally, an attention is also paid to the complexities of the KWS systems enabling them to potentially be exploited in real-detection tasks.
Keywords: Confidence Measure (CM), KeyWord Spotting (KWS), Spoken Term Detection (STD)
Projects Idiap
IM2
TA2
Authors Motlicek, Petr
Valente, Fabio
Szoke, Igor
Crossref by Motlicek_ICASSP_2012
Added by: [ADM]
Total mark: 0
Attachments
  • Motlicek_Idiap-RR-36-2012.pdf (MD5: ca628933cecc3efbcb6430c7acc4b0bd)
Notes