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GTTS System for the
Spoken Web Search Task
   at MediaEval 2012
Amparo Varona, Mikel Penagarikano, Luis Javier Rodríguez Fuentes,
                      Germán Bordel, Mireia Diez

             University of the Basque Country UPV/EHU
                     luisjavier.rodriguez@ehu.es
                            http://gtts.ehu.es



             MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
HEARCH: Search on Broadcast News
  (ASR + Lemmatization + Index)




         MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
HEARCH-P: Search on Parliamentary Sessions
     (Audio-Text Alignment + Index)




           MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
Search on spoken resources
         in the Internet
 • Searching for text queries (computer)
 • Searching for spoken queries (mobile)
 • Need for a common representation:
  • Acoustic (DTW-like approaches)
  • Phonetic (Search on Phone-Lattices)
  • Word-level (ASR-based approaches)
           MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
SWS at MediaEval 2012
     (for GTTS)
• Opportunity search onthe field resources
  unrestricted
               to enter
                        spoken
                                of

• Opportunity to access development and
  evaluation data
• Opportunity tofield state-of-the-art from
  experts in the
                 learn

• Our approach: search of the queries
  phonetic representations
                           of n-best

  on phone lattices of spoken resources
         MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
GTTS System: how it works



•   BUT decoders for Czech, Hungarian and Russian
•   Reduced sets of phonetic classes (IPA clusters)
•   Approximate string matching (n editions allowed):
    Dong Wang’s Lattice2Multigram tool
•   Scores: length-normalized + kind of log-likelihood ratio
    with regard to all the detections in the same audio file
•   Overlapped detections: only the most likely retained
•   For each query: K most likely detections, z-normalization
    and threshold applied
             MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
GTTS System: how it performs



 •   Best configurations determined in preliminary experiments
     on the development dataset
 •   Primary: 3-best query phone decodings, 2 editions allowed
     in matchings
 •   Contrastive: 1-best query phone decoding, 2 editions
     allowed in matchings
 •   Poor performance !!!
 •   Change in the approach: searching for the best detection of
     each query in each audio document
               MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
THANKS !!!

 MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012

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GTTS System for the Spoken Web Search Task at MediaEval 2012

  • 1. GTTS System for the Spoken Web Search Task at MediaEval 2012 Amparo Varona, Mikel Penagarikano, Luis Javier Rodríguez Fuentes, Germán Bordel, Mireia Diez University of the Basque Country UPV/EHU luisjavier.rodriguez@ehu.es http://gtts.ehu.es MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
  • 2. HEARCH: Search on Broadcast News (ASR + Lemmatization + Index) MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
  • 3. HEARCH-P: Search on Parliamentary Sessions (Audio-Text Alignment + Index) MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
  • 4. Search on spoken resources in the Internet • Searching for text queries (computer) • Searching for spoken queries (mobile) • Need for a common representation: • Acoustic (DTW-like approaches) • Phonetic (Search on Phone-Lattices) • Word-level (ASR-based approaches) MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
  • 5. SWS at MediaEval 2012 (for GTTS) • Opportunity search onthe field resources unrestricted to enter spoken of • Opportunity to access development and evaluation data • Opportunity tofield state-of-the-art from experts in the learn • Our approach: search of the queries phonetic representations of n-best on phone lattices of spoken resources MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
  • 6. GTTS System: how it works • BUT decoders for Czech, Hungarian and Russian • Reduced sets of phonetic classes (IPA clusters) • Approximate string matching (n editions allowed): Dong Wang’s Lattice2Multigram tool • Scores: length-normalized + kind of log-likelihood ratio with regard to all the detections in the same audio file • Overlapped detections: only the most likely retained • For each query: K most likely detections, z-normalization and threshold applied MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
  • 7. GTTS System: how it performs • Best configurations determined in preliminary experiments on the development dataset • Primary: 3-best query phone decodings, 2 editions allowed in matchings • Contrastive: 1-best query phone decoding, 2 editions allowed in matchings • Poor performance !!! • Change in the approach: searching for the best detection of each query in each audio document MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012
  • 8. THANKS !!! MediaEval 2012 - SWS Task - GTTS System - Pisa, October 4, 2012