D
David A. van Leeuwen
Researcher at Radboud University Nijmegen
Publications - 86
Citations - 2445
David A. van Leeuwen is an academic researcher from Radboud University Nijmegen. The author has contributed to research in topics: Speaker recognition & Speaker diarisation. The author has an hindex of 28, co-authored 81 publications receiving 2233 citations. Previous affiliations of David A. van Leeuwen include Netherlands Organisation for Applied Scientific Research.
Papers
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Journal ArticleDOI
Quenching of magnetic moments by ligand-metal interactions in nanosized magnetic metal clusters.
David A. van Leeuwen,J. M. van Ruitenbeek,L.J. de Jongh,A. Ceriotti,Gianfranco Pacchioni,O. D. Häberlen,Notker Rösch +6 more
TL;DR: In this paper, local density functional calculations and experimental magnetization studies on giant nickel carbonyl clusters are presented, and the results show convincingly that the effect of the carbonyls ligation is to quench completely the magnetic moments of the nickel atoms at the surface of the clusters, leaving the inner core metal atoms relatively unaffected.
Journal ArticleDOI
Automatic discrimination between laughter and speech
TL;DR: The development of a gender-independent laugh detector is described with the aim to enable automatic emotion recognition and acoustic measurements showed differences between laughter and speech in mean pitch and in the ratio of the durations of unvoiced to voiced portions, which indicate that these prosodic features are indeed useful for discrimination between laughed and speech.
Proceedings ArticleDOI
The RedDots Data Collection for Speaker Recognition
Kong Aik Lee,Anthony Larcher,Guangsen Wang,Patrick Kenny,Niko Brümmer,David A. van Leeuwen,Hagai Aronowitz,Marcel Kockmann,Carlos Vaquero,Bin Ma,Haizhou Li,Themos Stafylakis,Md. Jahangir Alam,Albert Swart,Javier Pérez +14 more
TL;DR: This paper describes data collection efforts conducted as part of the RedDots project which is dedicated to the study of speaker recognition under conditions where test utterances are of short duration and of variable phonetic content.
Proceedings ArticleDOI
Duration mismatch compensation for i-vector based speaker recognition systems
TL;DR: The effect of duration variability on phoneme distributions of speech utterances and i-vector length is analyzed and it is demonstrated that, as utterance duration is decreased, number of detected unique phonemes andi- vector length approaches zero in a logarithmic and non-linear fashion.
Proceedings ArticleDOI
On calibration of language recognition scores
TL;DR: A simple global calibration metric is proposed that can be generally applied to a multiple-hypothesis problem and it is demonstrated experimentally on some NIST-LRE-'05 data how this relates to the calibration of some of the derived binary-hypotheses sub-problems.