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

Autor
Zewoudie, A. W.; Jordi Luque; Hernando, J.
Tipus d'activitat
Article en revista
Revista
EURASIP Journal on Audio Speech and Music Processing
Data de publicació
2018-09-26
Volum
2018
Número
1
Pàgina inicial
1
Pàgina final
11
DOI
https://doi.org/10.1186/s13636-018-0140-x Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/123773 Obrir en finestra nova
URL
https://link.springer.com/article/10.1186/s13636-018-0140-x Obrir en finestra nova
Resum
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...
Paraules clau
Clustering, Cosine-distance, Fusion, GNE, Jitter, PLDA, Prosody, Segmentation, Shimmer, i-Vector
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
TALP - Centre de Tecnologies i Aplicacions del Llenguatge i la Parla
VEU - Grup de Tractament de la Parla

Participants