AUDIAS-CEU: A Language-independent approach for the Query-by-Example Spoken Term Detection task of the Search on Speech ALBAYZIN 2018 evaluation

Maria Cabello, Doroteo T. Toledano, Javier Tejedor


Query-by-Example Spoken Term Detection is the task of detecting query occurrences within speech data (henceforth utterances). Our submission is based on a language-independent template matching approach. First, queries and utterances are represented as phonetic posteriorgrams computed for English language with the phoneme decoder developed by the Brno University of Technology. Next, the Subsequence Dynamic Time Warping algorithm with a modified Pearson correlation coefficient as cost measure is employed to hipothesize detections. Results on development data showed an ATWV=0.1774 with MAVIR data and an ATWV=0.0365 with RTVE data.


 DOI: 10.21437/IberSPEECH.2018-51

Cite as: Cabello, M., T. Toledano, D., Tejedor, J. (2018) AUDIAS-CEU: A Language-independent approach for the Query-by-Example Spoken Term Detection task of the Search on Speech ALBAYZIN 2018 evaluation. Proc. IberSPEECH 2018, 245-248, DOI: 10.21437/IberSPEECH.2018-51.


@inproceedings{Cabello2018,
  author={Maria Cabello and Doroteo {T. Toledano} and Javier Tejedor},
  title={{AUDIAS-CEU: A Language-independent approach for the Query-by-Example Spoken Term Detection task of the Search on Speech ALBAYZIN 2018 evaluation}},
  year=2018,
  booktitle={Proc. IberSPEECH 2018},
  pages={245--248},
  doi={10.21437/IberSPEECH.2018-51},
  url={http://dx.doi.org/10.21437/IberSPEECH.2018-51}
}