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pro vyhledávání: '"Álvarez, Aitor"'
Autor:
Martín-Doñas, Juan M., Roselló, Eros, Gomez, Angel M., Álvarez, Aitor, López-Espejo, Iván, Peinado, Antonio M.
This paper presents the work carried out by the ASASVIcomtech team, made up of researchers from Vicomtech and University of Granada, for the ASVspoof5 Challenge. The team has participated in both Track 1 (speech deepfake detection) and Track 2 (spoof
Externí odkaz:
http://arxiv.org/abs/2408.10361
This paper describes our proposed integration system for the spoofing-aware speaker verification challenge. It consists of a robust spoofing-aware verification system that use the speaker verification and antispoofing embeddings extracted from specia
Externí odkaz:
http://arxiv.org/abs/2204.01399
Autor:
Martín-Doñas, Juan M., Álvarez, Aitor
This paper describes our submitted systems to the 2022 ADD challenge withing the tracks 1 and 2. Our approach is based on the combination of a pre-trained wav2vec2 feature extractor and a downstream classifier to detect spoofed audio. This method exp
Externí odkaz:
http://arxiv.org/abs/2203.01573
This article presents a full end-to-end pipeline for Arabic Dialect Identification (ADI) using intonation patterns and acoustic representations. Recent approaches to language and dialect identification use linguistic-aware deep architectures that are
Externí odkaz:
http://arxiv.org/abs/2008.00667
Flamenco singing is characterized by pitch instability, micro-tonal ornamentations, large vibrato ranges, and a high degree of melodic variability. These musical features make the automatic identification of flamenco singers a difficult computational
Externí odkaz:
http://arxiv.org/abs/2008.00198
In this paper we present an attentional neural network for folk song classification. We introduce the concept of musical motif embedding, and show how using melodic local context we are able to model monophonic folk song motifs using the skipgram ver
Externí odkaz:
http://arxiv.org/abs/1904.11074
This article presents a distributed vector representation model for learning folksong motifs. A skip-gram version of word2vec with negative sampling is used to represent high quality embeddings. Motifs from the Essen Folksong collection are compared
Externí odkaz:
http://arxiv.org/abs/1903.08756
Autor:
Martínez, Raquel, Carrillo-Carrión, Carolina, Destito, Paolo, Alvarez, Aitor, Tomás-Gamasa, María, Pelaz, Beatriz, Lopez, Fernando, Mascareñas, José L., del Pino, Pablo
Publikováno v:
In Cell Reports Physical Science 24 June 2020 1(6)
Autor:
Polo, Ester, Araban, Vida, Pelaz, Beatriz, Alvarez, Aitor, Taboada, Pablo, Mahmoudi, Morteza, del Pino, Pablo
Publikováno v:
In Applied Materials Today June 2019 15:599-604
Akademický článek
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