Publikace
Detail publikace
Citace
p. 457-464, Springer, Berlin-Heidelberg, Germany, 2013. : SVM-Based Detection of Misannotated Words in Read Speech Corpora . Text, Speech and Dialogue, Proceedings of the 16th International Conference TSD 2013, Lecture Notes in Artificial Intelligence, vol. 8082,
Další informace
Abstrakt
Automatic detection of misannotated words in single-speaker read-speech corpora is investigated in this paper. Support vector machine (SVM) classifier was proposed to detect the misannotated words. Its performance was evaluated with respect to various word-level feature sets. The SVM classifier was shown to perform very well with both high precision and recall scores and with F1 measure being almost 88%. This is a statistically significant improvement over a traditionally used outlier-based detection method.
Detail publikace
Název: | SVM-Based Detection of Misannotated Words in Read Speech Corpora |
---|---|
Autor: | Matoušek, J ; Tihelka, D. |
Název - česky: | Detekce chybně anotovaných slov v kopusech čtené řeči pomocí SVM |
Jazyk publikace: | anglicky |
Datum vydání: | 5.9.2013 |
Rok vydání: | 2013 |
Typ publikace: | Článek z časopisu |
Název knihy: | Text, Speech and Dialogue, Proceedings of the 16th International Conference TSD 2013 |
Svazek: | Lecture Notes in Artificial Intelligence |
Číslo vydání: | 8082 |
Strana: | 457 - 464 |
DOI: | 10.1007/978-3-642-40585-3_58 |
ISSN: | 0302-9743 |
Nakladatel: | Springer |
Místo vydání: | Berlin-Heidelberg, Germany |
Datum: | 1.9.2013 - 5.9.2013 |
Klíčová slova
annotation error detection, classification, support vector machine, read speech corpora
BibTeX
@INCOLLECTION{MatousekJ_2013_SVM-BasedDetection, author = {Matou\v{s}ek, J and Tihelka, D.}, title = {SVM-Based Detection of Misannotated Words in Read Speech Corpora}, year = {2013}, publisher = {Springer}, address = {Berlin-Heidelberg, Germany}, volume = {8082}, pages = {457-464}, booktitle = {Text, Speech and Dialogue, Proceedings of the 16th International Conference TSD 2013}, series = {Lecture Notes in Artificial Intelligence}, ISSN = {0302-9743}, doi = {10.1007/978-3-642-40585-3_58}, url = {http://www.kky.zcu.cz/en/publications/MatousekJ_2013_SVM-BasedDetection}, }