Attention based temporal filtering of sensory signals for data redundancy reduction

Sofoklis Kakouros, Okko Räsänen, Unto K. Laine

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

2 Sitaatiot (Scopus)

Abstrakti

Since modern computational devices are required to store and process increasing amounts of data generated from various sources, efficient algorithms for identification of significant information in the data are becoming essential. Sensory recordings are one example where automatic and continuous storing and processing of large amounts of data is needed. Therefore, algorithms that can alleviate the computational load of the devices and reduce their storage requirements by removing uninformative data are important. In this work we propose a method for data reduction based on theories of human attention. The method detects temporally salient events based on the context in which they occur and retains only those sections of the input signal. The algorithm is tested as a pre-processing stage in a weakly supervised keyword learning experiment where it is shown to significantly improve the quality of the codebooks used in the pattern discovery process.

AlkuperäiskieliEnglanti
Otsikko2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Sivut3188-3192
Sivumäärä5
DOI - pysyväislinkit
TilaJulkaistu - 18 lokak. 2013
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE International Conference on Acoustics, Speech, and Signal Processing - Vancouver, Kanada
Kesto: 26 toukok. 201331 toukok. 2013
Konferenssinumero: 38

Conference

ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing
LyhennettäICASSP
Maa/AlueKanada
KaupunkiVancouver
Ajanjakso26/05/201331/05/2013

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