ASAP: a Dataset of Aligned Scores and Performances for Piano Transcription

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BackgroundInterstitial lung diseases (ILD), such as idiopathic pulmonary fibrosis (IPF) and non-specific interstitial pneumonia (NSIP), and chronic obstructive pulmonary disease (COPD) are severe, progressive pulmonary disorders with a poor prognosis. Prom ...

In comparison to computational linguistics, with its abundance of natural-language datasets, corpora of music analyses are rather fewer and generally smaller. This is partly due to difficulties inherent to the encoding of music analyses, whose multimodal r ...

Reciprocity guarantees that in most media, sound transmission is symmetric between two points of space when the location of the source and receiver are interchanged. This fundamental law can be broken in non-linear media, often at the cost of detrimental i ...

Understanding the influence of running-induced acute fatigue on the homeostasis of the body is essential to mitigate the adverse effects and optimize positive adaptations to training. Fatigue is a multifactorial phenomenon, which influences biomechanical, ...

We investigate the design of a convolutional layer where kernels are parameterized functions. This layer aims at being the input layer of convolutional neural networks for audio applications or applications involving time-series. The kernels are defined as ...

Voice activity detection (VAD) is an important pre-processing step for speech technology applications. The task consists of deriving segment boundaries of audio signals which contain voicing information. In recent years, it has been shown that voice source ...

New materialism considers that the world and its histories are produced by a range of material forces that extend from the physical and the biological to the psychological, social and cultural. In recognizing that heritage is not held in objects alone, new ...

This paper introduces a novel approach for extracting speaker embeddings from audio mixtures of multiple overlapping voices. This approach is based on a multi-task neural network. The network first extracts a latent feature for each direction. This feature ...

The present paper discusses the climatic effects of humidity and temperature on cochlear implant functioning and the quality of the electrical sound signal. MATLAB Simulink simulations were prepared, offering insights into signal behavior under such climat ...

Walsh-Hadamard based orthogonal sampling of signals is studied in this paper, and an application of this technique is presented. Using orthogonal sampling, a single analog-to-digital converter (ADC) only is sufficient to perform parallel (simultaneous) rec ...

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In this work we present a method to jointly separate active audio and visual structures on a given mixture. Blind Audiovisual Source Separation is achieved exploiting the coherence between a video signal and a one-microphone audio track. The efficient repr ...

For parametric stereo and multi-channel audio coding, it has been proposed to use level difference, time difference, and coherence cues between audio channels to represent the perceptual spatial features of stereo and multi-channel audio signals. In practi ...

We address the problem of distributed compression in acoustic sensor networks. A typical scenario consists of a set of microphones that record a sound source located at some unknown position. The goal then is to convey the corresponding audio signals to a ...

The purpose of this thesis is to develop new methods for automatic transcription of melody and harmonic parts of real-life music signal. Music transcription is here defined as an act of analyzing a piece of music signal and writing down the parameter repre ...

A multimodal probabilistic framework is proposed for the problem of finding the active speaker in a video sequence. We localize the current speaker's mouth in the image by using the video and the audio channels together. We propose a novel visual feature t ...

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Audio segmentation, in general, is the task of segmenting a continuous audio stream in terms of acoustically homogenous regions, where the rule of homogeneity depends on the task. This thesis aims at developing and investigating efficient, robust and unsup ...

The recent advance of computer technology pushed the computing power of the modern computer systems to unprecedented levels; modern processors moved from the conventional, scalar type of architecture to more sophisticated, parallel ones, combining fast pro ...

ASAP: a Dataset of Aligned Scores and Performances for Piano Transcription

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Deep learning diagnostic and severity-stratification for interstitial lung diseases and chronic obstructive pulmonary disease in digital lung auscultations and ultrasonography: clinical protocol for an observational case-control study

MuseReduce: A Generic Framework for Hierarchical Music Analysis

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Learnable filter-banks for CNN-based audio applications

Unsupervised Voice Activity Detection by Modeling Source and System Information using Zero Frequency Filtering

Radical Intangibles: Materializing the Ephemeral

Multi-task Neural Network for Robust Multiple Speaker Embedding Extraction

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Walsh-Hadamard-Based Orthogonal Sampling Technique for Parallel Neural Recording Systems

Design Patterns for Resource-Constrained Automated Deep-Learning Methods

Blind Audiovisual Source Separation Using Sparse Representations

Improved Time Delay Analysis/Synthesis for Parametric Stereo Audio Coding

Distributed Compression in Acoustic Sensor Networks Using Oversampled A/D Conversion

Feature extraction of musical content for automatic music transcription

Multimodal Speaker Localization in a Probabilistic Framework

Audiovisual Gestalts

On the Use of Masking Models for Image and Audio Watermarking

Robust audio segmentation

A flexible framework for efficient design of advanced 3D audio systems in multimedia applications