Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Eiad Almekhlafi"'
Autor:
Ephrem Afele Retta, Richard Sutcliffe, Jabar Mahmood, Michael Abebe Berwo, Eiad Almekhlafi, Sajjad Ahmad Khan, Shehzad Ashraf Chaudhry, Mustafa Mhamed, Jun Feng
Publikováno v:
Applied Sciences, Vol 13, Iss 23, p 12587 (2023)
In a conventional speech emotion recognition (SER) task, a classifier for a given language is trained on a pre-existing dataset for that same language. However, where training data for a language do not exist, data from other languages can be used in
Externí odkaz:
https://doaj.org/article/95ae339e168a4471be069f63e45f3bff
Kiñit classification in Ethiopian chants, Azmaris and modern music: A new dataset and CNN benchmark.
Autor:
Ephrem Afele Retta, Richard Sutcliffe, Eiad Almekhlafi, Yosef Kefyalew Enku, Eyob Alemu, Tigist Demssice Gemechu, Michael Abebe Berwo, Mustafa Mhamed, Jun Feng
Publikováno v:
PLoS ONE, Vol 18, Iss 4, p e0284560 (2023)
In this paper, we create EMIR, the first-ever Music Information Retrieval dataset for Ethiopian music. EMIR is freely available for research purposes and contains 600 sample recordings of Orthodox Tewahedo chants, traditional Azmari songs and contemp
Externí odkaz:
https://doaj.org/article/3834e1af0a3b4395924bac229f06b46e
Autor:
Ephrem Afele Retta, Eiad Almekhlafi, Jun Feng, Xia Sun, Richard F. E. Sutcliffe, Mustafa Mhamed
Publikováno v:
Computational Intelligence and Neuroscience
Computational Intelligence and Neuroscience, Vol 2021 (2021)
Computational Intelligence and Neuroscience, Vol 2021 (2021)
Sentiment analysis is an essential process which is important to many natural language applications. In this paper, we apply two models for Arabic sentiment analysis to the ASTD and ATDFS datasets, in both 2-class and multiclass forms. Model MC1 is a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51512bdda183161475f670cd95be0ecf
https://doi.org/10.1155/2021/5538791
https://doi.org/10.1155/2021/5538791
In this paper we present the Amharic Speech Emotion Dataset (ASED), which covers four dialects (Gojjam, Wollo, Shewa and Gonder) and five different emotions (neutral, fearful, happy, sad and angry). We believe it is the first Speech Emotion Recogniti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8eb3f1b60d9d510356b025e96296f35d
Publikováno v:
International Journal of Electrical and Computer Engineering (IJECE). 12:2026
In computer vision, image classification is one of the potential image processing tasks. Nowadays, fish classification is a wide considered issue within the areas of machine learning and image segmentation. Moreover, it has been extended to a variety
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e305711b924bc4fba52b2827621866d
https://doi.org/10.11591/ijece.v12i2.pp2026-2039
https://doi.org/10.11591/ijece.v12i2.pp2026-2039
Publikováno v:
IEEE Transactions on Network and Service Management. :1-1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d35017834042c3e0a79e568d60ca11f1
https://doi.org/10.1109/tnsm.2022.3218127
https://doi.org/10.1109/tnsm.2022.3218127
Publikováno v:
Computer Speech & Language. 71:101274
Although the Arabic language is the fourth most popular language in the world, it has not received sufficient attention in artificial intelligence research, especially in automatic speech recognition (ASR). The key feature of the Arabic language is t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1cae072a972d2f0602111d8f6704c5a1
https://doi.org/10.1016/j.csl.2021.101274
https://doi.org/10.1016/j.csl.2021.101274