de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Datenschutzhinweis Impressum Kontakt
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Using temporal information for improving articulatory-acoustic feature classification

MPG-Autoren
Es sind keine MPG-Autoren in der Publikation vorhanden
Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)

90AA1BBCd01.pdf
(Verlagsversion), 312KB

Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Schuppler, B., van Doremalen, J., Scharenborg, O., Cranen, B., & Boves, L. (2009). Using temporal information for improving articulatory-acoustic feature classification. Automatic Speech Recognition and Understanding, IEEE 2009 Workshop, 70-75. doi:10.1109/ASRU.2009.5373314.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0012-D1F0-4
Zusammenfassung
This paper combines acoustic features with a high temporal and a high frequency resolution to reliably classify articulatory events of short duration, such as bursts in plosives. SVM classification experiments on TIMIT and SVArticulatory showed that articulatory-acoustic features (AFs) based on a combination of MFCCs derived from a long window of 25ms and a short window of 5ms that are both shifted with 2.5ms steps (Both) outperform standard MFCCs derived with a window of 25 ms and a shift of 10 ms (Baseline). Finally, comparison of the TIMIT and SVArticulatory results showed that for classifiers trained on data that allows for asynchronously changing AFs (SVArticulatory) the improvement from Baseline to Both is larger than for classifiers trained on data where AFs change simultaneously with the phone boundaries (TIMIT).