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The use of long-term features for GMM- and i-vector-based speaker diarization systems

Author
Zewoudie, A. W.; Jordi Luque; Hernando, J.
Type of activity
Journal article
Journal
EURASIP Journal on Audio Speech and Music Processing
Date of publication
2018-09-26
Volume
2018
Number
1
First page
1
Last page
11
DOI
https://doi.org/10.1186/s13636-018-0140-x Open in new window
Repository
http://hdl.handle.net/2117/123773 Open in new window
URL
https://link.springer.com/article/10.1186/s13636-018-0140-x Open in new window
Abstract
Several factors contribute to the performance of speaker diarization systems. For instance, the appropriate selection of speech features is one of the key aspects that affect speaker diarization systems. The other factors include the techniques employed to perform both segmentation and clustering. While the static mel frequency cepstral coefficients are the most widely used features in speech-related tasks including speaker diarization, several studies have shown the benefits of augmenting regul...
Citation
Zewoudie, A. W., Jordi Luque, Hernando, J. The use of long-term features for GMM- and i-vector-based speaker diarization systems. "EURASIP Journal on Audio Speech and Music Processing", 26 Setembre 2018, vol. 2018, núm. 1, p. 1-11.
Keywords
Clustering, Cosine-distance, Fusion, GNE, Jitter, PLDA, Prosody, Segmentation, Shimmer, i-Vector
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
TALP - Centre for Language and Speech Technologies and Applications
VEU - Speech Processing Group

Participants