Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Davies, Matthew"'
Publikováno v:
JCAP04(2024)050
Single-field models of inflation might lead to amplified scalar fluctuations on small scales due, for example, to a transient ultra-slow-roll phase. It was argued by Kristiano $\&$ Yokoyama in arXiv:2211.03395 that the enhanced amplitude of the scala
Externí odkaz:
http://arxiv.org/abs/2312.05694
To model the periodicity of beats, state-of-the-art beat tracking systems use "post-processing trackers" (PPTs) that rely on several empirically determined global assumptions for tempo transition, which work well for music with a steady tempo. For ex
Externí odkaz:
http://arxiv.org/abs/2308.10355
Self-supervision methods learn representations by solving pretext tasks that do not require human-generated labels, alleviating the need for time-consuming annotations. These methods have been applied in computer vision, natural language processing,
Externí odkaz:
http://arxiv.org/abs/2304.06868
For expressive music, the tempo may change over time, posing challenges to tracking the beats by an automatic model. The model may first tap to the correct tempo, but then may fail to adapt to a tempo change, or switch between several incorrect but p
Externí odkaz:
http://arxiv.org/abs/2210.06817
Publikováno v:
volume:10, year:2022, pages:44617-44626
In this paper we present a new approach for the generation of multi-instrument symbolic music driven by musical emotion. The principal novelty of our approach centres on conditioning a state-of-the-art transformer based on continuous-valued valence a
Externí odkaz:
http://arxiv.org/abs/2203.16165
Publikováno v:
JCAP06(2022)019
Working in an idealised framework in which a series of phases of evolution defined by the second slow-roll parameter $\eta$ are matched together, we calculate the reduced bispectrum, $f_{\rm NL}$, for models of inflation with a large peak in their pr
Externí odkaz:
http://arxiv.org/abs/2110.08189
Autor:
Sulun, Serkan, Davies, Matthew E. P.
In this paper, we address a sub-topic of the broad domain of audio enhancement, namely musical audio bandwidth extension. We formulate the bandwidth extension problem using deep neural networks, where a band-limited signal is provided as input to the
Externí odkaz:
http://arxiv.org/abs/2011.07274
In this paper, we present TIV.lib, an open-source library for the content-based tonal description of musical audio signals. Its main novelty relies on the perceptually-inspired Tonal Interval Vector space based on the Discrete Fourier transform, from
Externí odkaz:
http://arxiv.org/abs/2008.11529
Publikováno v:
Proc. of RecPad-2017, Amadora, Portugal, pp. 21-22, October, 2017
We address the task of advertisement detection in broadcast television content. While typically approached from a video-only or audio-visual perspective, we present an audio-only method. Our approach centres on the detection of short silences which e
Externí odkaz:
http://arxiv.org/abs/1811.02411
Publikováno v:
Proc. of RecPad-2017, Amadora, Portugal, pp. 19-20, October, 2017
The goal of this work is to develop an application that enables music producers to use their voice to create drum patterns when composing in Digital Audio Workstations (DAWs). An easy-to-use and user-oriented system capable of automatically transcrib
Externí odkaz:
http://arxiv.org/abs/1811.02406