Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Jakob Abeßer"'
Publikováno v:
Transactions of the International Society for Music Information Retrieval, Vol 5, Iss 1 (2022)
Given a music recording, music structure analysis aims at identifying important structural elements and segmenting the recording according to these elements. In jazz music, a performance is often structured by repeating harmonic schemata (known as ch
Externí odkaz:
https://doaj.org/article/e0ca4b3cd597468ba077eddb35c327b5
Publikováno v:
Empirical Musicology Review, Vol 11, Iss 1, Pp 68-82 (2016)
The metaphor of storytelling is widespread among jazz performers and jazz researchers. However, little is known about the precise meaning of this metaphor on an analytical level. The present paper attempts to shed light on the connected semantic fiel
Externí odkaz:
https://doaj.org/article/3f26601fb37047e6919bbf30c024d2be
Autor:
Jakob Abeßer
Publikováno v:
Applied Sciences, Vol 10, Iss 6, p 2020 (2020)
The number of publications on acoustic scene classification (ASC) in environmental audio recordings has constantly increased over the last few years. This was mainly stimulated by the annual Detection and Classification of Acoustic Scenes and Events
Externí odkaz:
https://doaj.org/article/b4e480e64ae546468cae653bb5c4db70
Publikováno v:
INTER-NOISE and NOISE-CON Congress and Conference Proceedings. 263:3324-3334
The development of robust acoustic traffic monitoring (ATM) algorithms based on machine learning faces several challenges. The biggest challenge is to collect and annotate large high-quality datasets for algorithm training and evaluation. Such a data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::40f8546bafb040e9efeefa69b39ef869
https://doi.org/10.3397/in-2021-2375
https://doi.org/10.3397/in-2021-2375
Autor:
Jakob Abesser, Meinard M{\\\'u}ller
The deployment of machine listening algorithms in real-life applications is often impeded by a domain shift caused for instance by different microphone characteristics. In this paper, we propose a novel domain adaptation strategy based on disentangle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a84537a0066c26e2acdaadd61ab0594f
http://arxiv.org/abs/2110.13586
http://arxiv.org/abs/2110.13586
Publikováno v:
Electronics, Vol 10, Iss 851, p 851 (2021)
Electronics
Volume 10
Issue 7
Electronics
Volume 10
Issue 7
In this work, we propose considering the information from a polyphony for multi-pitch estimation (MPE) in piano music recordings. To that aim, we propose a method for local polyphony estimation (LPE), which is based on convolutional neural networks (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68a026cb06513f261c3d0220acd80a0b
https://www.mdpi.com/2079-9292/10/7/851
https://www.mdpi.com/2079-9292/10/7/851
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030702090
CMMR
CMMR
Electroacoustic music is experienced primarily through auditory perception, as it is not usually based on a prescriptive score. For the analysis of such pieces, transcriptions are sometimes created to illustrate events and processes graphically in a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fbac864873f6ae81a829c04b218a940b
https://doi.org/10.1007/978-3-030-70210-6_3
https://doi.org/10.1007/978-3-030-70210-6_3
Publikováno v:
Audio Mostly Conference
In this paper, we investigate a previously proposed algorithm for spoken language identification based on convolutional neural networks and convolutional recurrent neural networks. We improve the algorithm by modifying the training strategy to ensure
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18b7184c23e13ce76d3d9347720d214f
https://doi.org/10.1145/3411109.3411123
https://doi.org/10.1145/3411109.3411123
Autor:
Jakob Abeßer, Gerald Schuller
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 25:1741-1750
This paper deals with the automatic transcription of solo bass guitar recordings with an additional estimation of playing techniques and fretboard positions used by the musician. Our goal is to first develop a system for a robust estimation of the no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31147860b35b7fd972544a0e085db69f
https://doi.org/10.1109/taslp.2017.2702384
https://doi.org/10.1109/taslp.2017.2702384
Autor:
Christof Weiss, Meinard Müller, Jakob Abeßer, Vlora Arifi-Müller, Stylianos Ioannis Mimilakis
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030438869
PKDD/ECML Workshops (2)
PKDD/ECML Workshops (2)
In this paper, we approach the problem of detecting segments of singing voice activity in opera recordings. We consider three state-of-the-art methods for singing voice detection based on supervised deep learning. We train and test these models on a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ce4b44425fbd6eb346e640f710bb233
https://doi.org/10.1007/978-3-030-43887-6_35
https://doi.org/10.1007/978-3-030-43887-6_35