9786138938583 - songs classification based on mood using low and high level features di nandanwar, prof. sneha; gandhi, prof. vaibhav c. (9 risultati)
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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EUR 73,72
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Condizione: New.
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Da: moluna, Greven, Germaniamoluna
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EUR 38,74
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
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Da: preigu, Osnabrück, Germaniapreigu
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EUR 40,25
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Songs Classification Based on Mood using Low and High Level Features | Sneha Nandanwar (u. a.) | Taschenbuch | Englisch | 2021 | Scholars' Press | EAN 9786138938583 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter:…preigu.
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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
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EUR 158,70
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paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 45,90
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Music has been associate inherent a part of human life once it involves recreation; entertainment and far recently, even as a therapeutic medium. The means by which music is composed and listened to has witnessed a huge transition…from the age of magnetic tape recorders to the recent age of digital music players streaming music from the cloud. What has remained intact is that the special relation that music shares with human emotions. We most frequently like better to hear a song or music which best suits our mood at that moment. In spite of this robust correlation, most of the music software existing nowadays are still barren of providing the ability of mood-aware play-list generation. This will increase the time music listeners soak in manually selecting category of songs fitting mood or occasion, which can be avoided by expanding upon songs with the relevant feeling class they convey. The downside, however, lies within the overhead of manual annotation of music with its corresponding mood and also the challenge is to spot this side mechanically and showing intelligence.We have analyzed many classification algorithms in order to be train and check the moods of audio songs. 68 pp. Englisch.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 74,53
EUR 7,59 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand.
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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EUR 74,73
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 45,90
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Music has been associate inherent a part of human life once it involves recreation; entertainment and far recently, even as a therapeutic medium. The means by which music is composed and listened to has witnessed a huge transition from… the age of magnetic tape recorders to the recent age of digital music players streaming music from the cloud. What has remained intact is that the special relation that music shares with human emotions. We most frequently like better to hear a song or music which best suits our mood at that moment. In spite of this robust correlation, most of the music software existing nowadays are still barren of providing the ability of mood-aware play-list generation. This will increase the time music listeners soak in manually selecting category of songs fitting mood or occasion, which can be avoided by expanding upon songs with the relevant feeling class they convey. The downside, however, lies within the overhead of manual annotation of music with its corresponding mood and also the challenge is to spot this side mechanically and showing intelligence.We have analyzed many classification algorithms in order to be train and check the moods of audio songs.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 46,45
EUR 60,60 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Music has been associate inherent a part of human life once it involves recreation; entertainment and far recently, even as a therapeutic medium. The means by which music is composed and listened to has witnessed a huge transition from…the age of magnetic tape recorders to the recent age of digital music players streaming music from the cloud. What has remained intact is that the special relation that music shares with human emotions. We most frequently like better to hear a song or music which best suits our mood at that moment. In spite of this robust correlation, most of the music software existing nowadays are still barren of providing the ability of mood-aware play-list generation. This will increase the time music listeners soak in manually selecting category of songs fitting mood or occasion, which can be avoided by expanding upon songs with the relevant feeling class they convey. The downside, however, lies within the overhead of manual annotation of music with its corresponding mood and also the challenge is to spot this side mechanically and showing intelligence.We have analyzed many classification algorithms in order to be train and check the moods of audio songs.
