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pro vyhledávání: '"audio content analysis"'
Autor:
Lerch, Alexander
The three packages libACA, pyACA, and ACA-Code provide reference implementations for basic approaches and algorithms for the analysis of musical audio signals in three different languages: C++, Python, and Matlab. All three packages cover the same al
Externí odkaz:
http://arxiv.org/abs/2206.15219
Autor:
Lerch, Alexander
Preprint for a book chapter introducing Audio Content Analysis. With a focus on Music Information Retrieval systems, this chapter defines musical audio content, introduces the general process of audio content analysis, and surveys basic approaches to
Externí odkaz:
http://arxiv.org/abs/2101.00132
Colombia has a diversity of genres in traditional music, which allows to express the richness of the Colombian culture according to the region. This musical diversity is the result of a mixture of African, native Indigenous, and European influences.
Externí odkaz:
http://arxiv.org/abs/1911.03372
Akademický článek
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Autor:
Vafeiadis, Anastasios a, b, ⁎, Votis, Konstantinos a, Giakoumis, Dimitrios a, Tzovaras, Dimitrios a, Chen, Liming b, Hamzaoui, Raouf b
Publikováno v:
In Engineering Applications of Artificial Intelligence March 2020 89
Autor:
Sager, Sebastian, Elizalde, Benjamin, Borth, Damian, Schulze, Christian, Raj, Bhiksha, Lane, Ian
Recently, sound recognition has been used to identify sounds, such as car and river. However, sounds have nuances that may be better described by adjective-noun pairs such as slow car, and verb-noun pairs such as flying insects, which are under explo
Externí odkaz:
http://arxiv.org/abs/1607.03766
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2018, Iss 1, Pp 1-12 (2018)
Abstract Recently, sound recognition has been used to identify sounds, such as the sound of a car, or a river. However, sounds have nuances that may be better described by adjective-noun pairs such as “slow car” and verb-noun pairs such as “fly
Externí odkaz:
https://doaj.org/article/58ff7e5a039f4655b122e82aedbd8bf4
Autor:
Kumar, Anurag, Raj, Bhiksha
Audio Event Detection is an important task for content analysis of multimedia data. Most of the current works on detection of audio events is driven through supervised learning approaches. We propose a weakly supervised learning framework which can m
Externí odkaz:
http://arxiv.org/abs/1606.03664
The goal of this research project is to undertake a critical evaluation of signal representations for musical audio content analysis. In particular it will contrast three different means for undertaking the analysis of micro-rhythmic content in Afro-
Externí odkaz:
https://hdl.handle.net/10216/132844