in English – Page 2 – Audio @ LS2N

Correlation of Fréchet Audio Distance With Human Perception of Environmental Audio Is Embedding Dependent @ EUSIPCO

This paper explores whether considering alternative domain-specific embeddings to calculate the Fréchet Audio Distance (FAD) metric can help the FAD to correlate better with perceptual ratings of environmental sounds. We used embeddings from VGGish, PANNs, MS-CLAP, L-CLAP, and MERT, which are tailored for either music or environmental sound evaluation. The FAD scores were calculated for sounds from the DCASE 2023 Task 7 dataset. Using perceptual data from the same task, we find that PANNs-WGM-LogMel produces the best correlation between FAD scores and perceptual ratings of both audio quality and perceived fit with a Spearman correlation higher than 0.5. We also find that music-specific embeddings resulted in significantly lower results. Interestingly, VGGish, the embedding used for the original Fréchet calculation, yielded a correlation below 0.1. These results underscore the critical importance of the choice of embedding for the FAD metric design.

BioacAI doctoral network workshop in Czech Republic

From May 6th to May 10th, 2024, PhD student Yasmine Benhamadi and CNRS scientist Vincent Lostanlen have attended the first internal workshop of the BioacAI doctoral network. The Czech University of Life Sciences in Prague hosted the event in its University Forest Establishment, an ancient castle in the town of Kostelec nad Černými lesy.

Action “Musiscale” au symposium du GDR MaDICS

Le 30 mai 2024 à Blois, se tenait le sixième symposium du GDR MaDICS : masses de données, informations et connaissances en sciences. Dans le cadre de l’action “Musiscale : modélisation multi-échelles de masses de données musicales”, j’ai présenté les travaux de l’équipe sur la diffusion en ondelettes (scattering transform) ainsi que sur les réseaux de neurones multirésolution (MuReNN pour multi-resolution neural networks).

Japanese–French Frontiers of Science Symposium 「日仏先端科学シンポジウム」

Towards multisensory control of physical modeling synthesis @ Inter-Noise

Physical models of musical instruments offer an interesting tradeoff between computational efficiency and perceptual fidelity. Yet, they depend on a multidimensional space of user-defined parameters whose exploration by trial and error is impractical. Our article addresses this issue by combining two ideas: query by example and gestural control. On one hand, we train a deep… Continue reading Towards multisensory control of physical modeling synthesis @ Inter-Noise

Structure Versus Randomness in Computer Music and the Scientific Legacy of Jean-Claude Risset @ JIM

According to Jean-Claude Risset (1938–2016), “art and science bring about complementary kinds of knowledge”. In 1969, he presented his piece Mutations as “[attempting] to explore […] some of the possibilities offered by the computer to compose at the very level of sound—to compose sound itself, so to speak.” In this article, I propose to take the same motto as a starting point, yet while adopting a mathematical and technological outlook, more so than a musicological one.

Instabilities in Convnets for Raw Audio @ IEEE SPL

What makes waveform-based deep learning so hard? Despite numerous attempts at training convolutional neural networks (convnets) for filterbank design, they often fail to outperform hand-crafted baselines. These baselines are linear time-invariant systems: as such, they can be approximated by convnets with wide receptive fields. Yet, in practice, gradient-based optimization leads to suboptimal approximations. In our… Continue reading Instabilities in Convnets for Raw Audio @ IEEE SPL

PhD offer: Machine learning on solar-powered environmental sensors

Many biological and geophysical phenomena follow a near-periodic day-night cycle, known as circadian rhythm. When designing AI-enabled autonomous sensors for environmental modeling, this circadian rhythm poses both a challenge and an opportunity.

PhD offer: Developmental robotics of birdsong

The Neurocybernetic team of ETIS Lab (CNRS, CY Cergy-Paris University, ENSEA) is seeking applicants for a fully funded PhD place providing an exciting opportunity to pursue a postgraduate research in the fields of bio/neuro-inspired robotics, ethology, neuroscience.Webpage: https://www.etis-lab.fr/neuro/ This PhD is funded by the French ANR, under the 4 years’ project “Nirvana” on sensorimotor integration of… Continue reading PhD offer: Developmental robotics of birdsong

Towards constructing a historically grounded gesture-timbre space of Guqin playing techniques @ Timbre

Guqin is an ancient Chinese zither instrument known for its timbral variability and the vital role timbre, as opposed to melody or rhythm, played in its classical compositions. Numerous ancient texts dating back to the 1500s provided gestural guidelines of defined Guqin playing techniques and recommendations on timbre aesthetics. It’s also suggested in these texts that small deviations in gestures have significant impact on resulting timbres. Nevertheless, traditionally and even today, Guqin pedagogies are largely metaphoric, mind instead of body, and include limited elaboration on recommended gestures. To digitize and concretize the sonic implications in Guqin gesture-timbre writings, and variegate within the oversimplified vocabulary of playing techniques, this study aims to design and record a dataset of isolated, short, representative Guqin sounds labeled by gestural data. The sounds in question are curated by extracting ancient text, where emphasis on gesture-induced timbral difference is mentioned. We decompose the notion of gesture into nine degrees of freedom for both hands, including left/right hand position, fingers used, point of contact, left/right hand temporal coordination, etc. We define a ladder of gestural data at various levels, ranging from discrete labels of playing techniques, the aforementioned degrees of freedom to continuous signals acquired by high-speed camera with automatic hand-tracking system. We analyze in time-frequency domain timbres resulting from conventional playing gestures and their systematically “perturbed” versions. We investigate the correlation between timbres and their underlying gestures, via methods derived from multidimensional scaling.