A Feature Learning Siamese Model for Intelligent Control of the Dynamic Range Compressor
, 2019 In this paper, a siamese DNN model is proposed to learn the characteristics of the audio dynamic range compressor (DRC). This facilitates an intelligent control system that uses audio examples to configure the DRC, a widely used non-linear audio signal ...
Fazekas, György, Sheng, Di
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Unsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging [PDF]
, 2016 Environmental audio tagging aims to predict only the presence or absence of certain acoustic events in the interested acoustic scene. In this paper we make contributions to audio tagging in two parts, respectively, acoustic modeling and feature learning.
Foster, Peter +6 more
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Eventness: Object Detection on Spectrograms for Temporal Localization of Audio Events
, 2018 In this paper, we introduce the concept of Eventness for audio event detection, which can, in part, be thought of as an analogue to Objectness from computer vision.
Das, Samarjit +3 more
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Noise MappingUrban environments are characterized by a complex interplay of various sound sources, which significantly influence the overall soundscape quality. This study presents a methodology that combines the intermittency ratio (IR) metric for acoustic event ...
Vidaña-Vila Ester +2 more
doaj +1 more source
Learning Audio Sequence Representations for Acoustic Event Classification
, 2017 Acoustic Event Classification (AEC) has become a significant task for machines to perceive the surrounding auditory scene. However, extracting effective representations that capture the underlying characteristics of the acoustic events is still ...
Han, Jing +4 more
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Cutting tracks, making CDs: a comparative study of audio time-correction techniques in the desktop age. [PDF]
, 2008 Producers have long sought to “tighten” studio performances. Software-based DAW’s now come with proprietary functions to facilitate this, but only the latest generation of platforms allow relative ease of use on longer takes.
Paterson, Justin
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Drum Transcription via Classification of Bar-level Rhythmic Patterns [PDF]
, 2014 acceptedMatthias Mauch is supported by a Royal Academy of Engineering Research ...
15th International Society for Music Information Retrieval Conference +3 more
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Deep Learning for Audio Signal Processing
, 2019 Given the recent surge in developments of deep learning, this article provides a review of the state-of-the-art deep learning techniques for audio signal processing.
Chang, Shuo-yiin +5 more
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DCASE 2018 Challenge Surrey Cross-Task convolutional neural network baseline [PDF]
, 2018 The Detection and Classification of Acoustic Scenes and Events (DCASE) consists of five audio classification and sound event detection tasks: 1) Acoustic scene classification, 2) General-purpose audio tagging of Freesound, 3) Bird audio detection, 4 ...
Iqbal, Turab +4 more
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USM-SED - A Dataset for Polyphonic Sound Event Detection in Urban Sound Monitoring Scenarios
, 2021 This paper introduces a novel dataset for polyphonic sound event detection in urban sound monitoring use-cases. Based on isolated sounds taken from the FSD50k dataset, 20,000 polyphonic soundscapes are synthesized with sounds being randomly positioned in the stereo panorama using different loudness levels.
openaire +2 more sources