Results 51 to 60 of about 102,254 (307)
Trends in Hearing, 2017 The purpose of this study was to test the hypothesis that listeners with frequent exposure to loud music exhibit deficits in suprathreshold auditory performance consistent with cochlear synaptopathy. Young adults with normal audiograms were recruited who
John H. Grose +2 more
doaj +1 more source
Throughput Scaling Of Convolution For Error-Tolerant Multimedia Applications
, 2012 Convolution and cross-correlation are the basis of filtering and pattern or template matching in multimedia signal processing. We propose two throughput scaling options for any one-dimensional convolution kernel in programmable processors by adjusting ...
Anam, Mohammad Ashraful +1 more
core +1 more source
High-dimensional sequence transduction [PDF]
, 2012 We investigate the problem of transforming an input sequence into a high-dimensional output sequence in order to transcribe polyphonic audio music into symbolic notation. We introduce a probabilistic model based on a recurrent neural network that is able
Bengio, Yoshua +2 more
core +2 more sources
The Sound Demixing Challenge 2023 – Music Demixing Track
Transactions of the International Society for Music Information RetrievalThis paper summarizes the music demixing (MDX) track of the Sound Demixing Challenge (SDX’23). We provide a summary of the challenge setup and introduce the task of robust music source separation (MSS), i.e., training MSS models in the presence of errors
Giorgio Fabbro +26 more
doaj +1 more source
Frequency Hopping Method for Audio Watermarking [PDF]
Telfor Journal, 2012 This paper evaluates the degradation of audio content for a perceptible removable watermark. Two different approaches to embedding the watermark in the spectral domain were investigated.
A. Anastasijević, D. Čoja
doaj
Hearing the Sound in the Brain: Influences of Different EEG References
Frontiers in Neuroscience, 2018 If the scalp potential signals, the electroencephalogram (EEG), are due to neural “singers” in the brain, how could we listen to them with less distortion?
Dan Wu, Dan Wu
doaj +1 more source
Query-based Deep Improvisation [PDF]
, 2019 In this paper we explore techniques for generating new music using a Variational Autoencoder (VAE) neural network that was trained on a corpus of specific style. Instead of randomly sampling the latent states of the network to produce free improvisation,
Dubnov, Shlomo
core +1 more source
Distorted sounds: unlocking the physics of modern music
European Journal of PhysicsAbstract In the production of modern music, the musical characteristics of the guitar or keyboard amplifier play an integral role in the creative process. This article explores the physics of music with an emphasis on the role of distortion in amplification. In particular, we derive and illustrate how a distorted amplifier creates new
Anna Mullin, Derek B Leinweber
openaire +2 more sources
Advanced Functional Materials, EarlyView.A pixelation‐free, monolithic iontronic pressure sensor enables simultaneous pressure and position sensing over large areas. AC‐driven ion release generates spatially varying impedance pathways depending on the pressure. Machine learning algorithms effectively decouple overlapping pressure–position signals from the multichannel outputs, achieving high ...
Juhui Kim +10 more
wiley +1 more source
Deep Music Information Dynamics
Journal of Creative Music Systems, 2022 Generative musical models often comprise of multiple levels of structure, presuming that the process of composition moves between background to foreground, or between generating musical surface and some deeper and reduced representation that governs ...
Shlomo Dubnov, Ke Chen, Kevin Huang
doaj +1 more source