Skip to main content
zenodoopen

GRB assessment of the Saarbrücken Voice Database

<p>GRB&nbsp;evaluations of the Saarbruecken database. Annex to the paper:&nbsp;<em>Multimodal and multi-output deep learning architectures for the automatic assessment of voice quality using the GRB scale.&nbsp;</em></p> <p>Published in&nbsp;IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, VOL. 14, NO. 2, FEBRUARY 2020:&nbsp;<strong>DOI:&nbsp;</strong><a href="https://doi.org/10.1109/JSTSP.2019.2956410">10.1109/JSTSP.2019.2956410</a>&nbsp;<br> &nbsp;</p> <p>If you use these labels&nbsp;please cite as:</p> <p>J. D. Arias-Londo&ntilde;o, J. A. G&oacute;mez-Garc&iacute;a and J. I. Godino-Llorente, &quot;Multimodal and Multi-Output Deep Learning Architectures for the Automatic Assessment of Voice Quality Using the GRB Scale,&quot; in&nbsp;<em>IEEE Journal of Selected Topics in Signal Processing</em>, vol. 14, no. 2, pp. 413-422, Feb. 2020.</p>

ShareScore

44/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
8
Access
16
Reuse readiness
8
Engagement
4

Topics

Dataset details

Repository
zenodo
Published
November 21, 2019
License
cc-by-4.0
DOI
10.5281/zenodo.3550735

Scored with release 0.9.0

ScienceDex for faculty

Your academic CV and NIH biosketch

Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.