The purpose of this paper is to show a music mixing system that is capable of automatically mixing separate raw recordings with good quality regardless of the music genre. This work recalls selected methods for automatic audio mixing first. Then, a novel deep model based on one-dimensional Wave-U-Net autoencoders is proposed for automatic music mixing. The model is trained on a custom-prepared database. Mixes created using the...

The purpose of this dissertation is to develop an automatic song mixing system that is capable of automatically mixing a song with good quality in any music genre. This work recalls first the audio signal processing methods used in audio mixing, and it describes selected methods for automatic audio mixing. Then, a novel architecture built based on one-dimensional Wave-U-Net autoencoders is proposed for automatic music mixing. Models...

The aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...

The paper analyzes some properties of denoising autoencoders using the problem of misspellings correction as an exemplary task. We evaluate the capacity of the network in its classical feed-forward form. We also propose a modification to the output layer of the net, which we called multi-softmax. Experiments show that the model trained with this output layer outperforms traditional network both in learning time and accuracy. We...

An approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...