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

Related publications (23)

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

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 ...

BMC2023

MuseReduce: A Generic Framework for Hierarchical Music Analysis

Martin Alois Rohrmeier, Petter Harald Ericson

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 ...

Humanities Commons2023

Observation of non-reciprocal harmonic conversion in real sounds

Romain Christophe Rémy Fleury, Hervé Lissek, Xinxin Guo

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 ...

2023

Concurrent Evolution of Biomechanical and Physiological Parameters With Running-Induced Acute Fatigue

Kamiar Aminian, Anisoara Ionescu, Salil Apte, Gaëlle Prigent

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, ...

FRONTIERS MEDIA SA2022

Learnable filter-banks for CNN-based audio applications

Benjamin Ricaud, Nicolas Aspert, Helena Peic Tukuljac

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 ...

2022

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

Mathew Magimai Doss, Eklavya Sarkar

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 ...

ISCA2022

Radical Intangibles: Materializing the Ephemeral

Sarah Irene Brutton Kenderdine, Lillian Hibberd

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 ...

2021

Multi-task Neural Network for Robust Multiple Speaker Embedding Extraction

Jean-Marc Odobez, Petr Motlicek, Weipeng He

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 ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Electrical Signal Modeling in Cochlear Implants. Study of Temperature and Humidity Effects

Maria-Alexandra Paun

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 ...

MDPI2021

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

Alexandre Schmid, Reza Ranjandish

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 ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Design Patterns for Resource-Constrained Automated Deep-Learning Methods

Prakhar Gupta

We present an extensive evaluation of a wide variety of promising design patterns for automated deep-learning (AutoDL) methods, organized according to the problem categories of the 2019 AutoDL challenges, which set the task of optimizing both model accurac ...

2020

Multisensory haptic system and method

Olaf Blanke, Giulio Rognini, Simon Gallo

A computer-implemented method for operating a haptic device, the haptic device comprising a plurality of tactile displays configured to provide haptic stimuli to a user, the method including the steps of (a) processing an audio signal derived from an audio ...

2020

Sparse and Parametric Modeling with Applications to Acoustics and Audio

Helena Peic Tukuljac

Recent advances in signal processing, machine learning and deep learning with sparse intrinsic structure of data have paved the path for solving inverse problems in acoustics and audio. The main task of this thesis was to bridge the gap between the powerfu ...

EPFL2020

Single-molecule sensing of peptides and nucleic acids by engineered aerolysin nanopores

Aleksandra Radenovic, Matteo Dal Peraro, Chan Cao

Nanopore sensing is a powerful single-molecule approach for the detection of biomolecules. Recent studies have demonstrated that aerolysin is a promising candidate to improve the accuracy of DNA sequencing and to develop novel single-molecule proteomic str ...

Nature Research2019

Inpainting of Long Audio Segments With Similarity Graphs

Nathanaël Perraudin

We present a novel method for the compensation of long duration data loss in audio signals, in particular music. The concealment of such signal defects is based on a graph that encodes signal structure in terms of time-persistent spectral similarity. A sui ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Deep Learning of Human Perception in Audio Event Classification

Samuel Denys Beuret

In this paper, we introduce our recent studies on human perception in audio event classification. In particular, the pre-trained model VGGish is used as feature extractor to process audio data, and DenseNet is trained by and used as feature extractor for o ...

IEEE2018

Experimental evaluation of speech enhancement methods in remote microphone systems for hearing aids

Hervé Lissek, Ina Kodrasi, Gilles André Courtois, Vincent Pierre Olivier Grimaldi

Enhancing speech intelligibility for hearing-impaired subjects in complex acoustic conditions is still a challenging topic of research. To mitigate the detrimental effects of background noise and reverberation, current hearing instruments incorporate vario ...

European Acoustics Association2018

A 4-channel 5.04 μW 0.325 mm2 Orthogonal Sampling-Based Parallel Neural Recording System

Alexandre Schmid, Reza Ranjandish

The application of orthogonal sampling for parallel neural recording is presented in this paper. Orthogonal sampling enables reducing the number of the I Cs in conventional recording systems into one single unit. Consequently, the ADC bandwidth and dynamic ...

IEEE2018

Method and apparatus for presenting to a user of a wearable apparatus additional information related to an audio scene

Martin Vetterli, Ivan Dokmanic, Juri Ranieri

A method for presenting to a user of a wearable audio device a modified audio scene together with additional information related to the audio scene, comprising: capturing audio signals with a plurality of microphones; outputting an audio signal with a plur ...

2017

System fusion and speaker linking for longitudinal diarization of TV shows

Hervé Bourlard, Petr Motlicek

Performing speaker diarization while uniquely identifying the speakers in a collection of audio recordings is a challenging task. Based on our previous work on speaker diarization and linking, we developed a system for diarizing longitudinal TV show data s ...

IEEE2016