Anzeige
Erschienen in:
2006 | OriginalPaper | Buchkapitel
Integrating Complementary Features with a Confidence Measure for Speaker Identification
verfasst von : Nengheng Zheng, P. C. Ching, Ning Wang, Tan Lee
Erschienen in: Chinese Spoken Language Processing
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
This paper investigates the effectiveness of integrating complementary acoustic features for improved speaker identification performance. The complementary contributions of two acoustic features, i.e. the conventional vocal tract related features MFCC and the recently proposed vocal source related features WOCOR, for speaker identification are studied. An integrating system, which performs a score level fusion of MFCC and WOCOR with a confidence measure as the weighting parameter, is proposed to take full advantage of the complementarity between the two features. The confidence measure is derived based on the speaker discrimination powers of MFCC and WOCOR in each individual identification trial so as to give more weight to the one with higher confidence in speaker discrimination. Experiments show that information fusion with such a confidence measure based varying weight outperforms that with a pre-trained fixed weight in speaker identification.