Kymatio: Scattering Transforms in Python

The wavelet scattering transform is an invariant signal representation suitable for many signal processing and machine learning applications. We present the Kymatio software package, an easy-to-use, high-performance Python implementation of the scattering transform in 1D, 2D, and 3D that is compatible with modern deep learning frameworks. All transforms may be executed on a GPU (in addition to CPU), offering a considerable speed up over CPU implementations. The package also has a small memory footprint, resulting inefficient memory usage. The source code, documentation, and examples are available undera BSD license at https://www.kymat.io

A djuvant treatment in patients at high risk of recurrence of thymoma: Efficacy and safety of a three-dimensional conformal radiation therapy regimen

The clinical benefits of postoperative radiation therapy (PORT) for patients with thymoma are still controversial. In the absence of defined guidelines, prognostic factors such as stage, status of surgical margins, and histology are often considered to guide the choice of adjuvant treatment (radiotherapy and/or chemotherapy). In this study, we describe our single-institution experience of three-dimensional conformal PORT administered as adjuvant treatment to patients with thymoma. METHODS: Twenty-two consecutive thymoma patients (eleven male and eleven female) with a median age of 52 years and treated at our institution by PORT were analyzed. The patients were considered at high risk of recurrence, having at least one of the following features: stage IIB or III, involved resection margins, or thymic carcinoma histology. Three-dimensional conformal PORT with a median total dose on clinical target volume of 50 (range 44-60) Gy was delivered to the tumor bed by 6-20 MV X-ray of the linear accelerator. Follow-up after radiotherapy was done by computed tomography scan every 6 months for 2 years and yearly thereafter. RESULTS: Two of the 22 patients developed local recurrence and four developed distant metastases. Median overall survival was 100 months, and the 3-year and 5-year survival rates were 83% and 74%, respectively. Median disease-free survival was 90 months, and the 5-year recurrence rate was 32%. On univariate analysis, pathologic stage III and presence of positive surgical margins had a significant impact on patient prognosis. Radiation toxicity was mild in most patients and no severe toxicity was registered. CONCLUSION: Adjuvant radiotherapy achieved good local control and showed an acceptable toxicity profile in patients with high-risk thymoma

Imitative Computer-Aided Musical Orchestration with Biologically Inspired Algorithms

International audienceMusical orchestration is an empirical art form based on tradition and heritage whose lack of formalism hinders the development of assisstive computational tools. Computer-aided musical orchestration (CAMO) systems aim to assist the composer in several steps of the orchestration procedure. Particularly, imitative CAMO focuses on instrumentation by aiding the composer in creating timbral mixtures as instrument combinations. Imitative CAMO allows composers to specify a reference sound and replicate it with a predetermined orchestr

Imitative Computer-Aided Musical Orchestration with Biologically Inspired Algorithms

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Estimating unobserved audio features for target-based orchestration

Target-based assisted orchestration can be thought of as the process of searching for optimal combinations of sounds to match a target sound, given a database of samples, a similarity metric, and a set of constraints. A typical solution to this problem is a proposed orchestral score where candidates are ranked by similarity in some feature space between the target sound and the mixture of audio samples in the database corresponding to the notes in the score; in the orchestral setting, valid scores may contain dozens of instruments sounding simultaneously. Generally, target-based assisted orchestration systems consist of a combinatorial optimization algorithm and a constraint solver that are jointly optimized to find valid solutions. A key step in the optimization involves generating a large number of combinations of sounds from the database and then comparing the features of each mixture of sounds with the target sound. Because of the high computational cost required to synthesize a new audio file and then compute features for every combination of sounds, in practice, existing systems instead estimate the features of each new mixture using precomputed features of the individual source files making up the combination. Currently, state-of-the-art systems use a simple linear combination to make these predictions, even if the features in use are not themselves linear. In this work, we explore neural models for estimating the features of a mixture of sounds from the features of the component sounds, finding that standard features can be estimated with accuracy significantly better than that of the methods currently used in assisted orchestration systems. We present quantitative comparisons and discuss the implications of our findings for target-based orchestration problems

Vivace: Web Application for Real-Time feedback on Piano Performance

International audienceSoftware that provide feedback on music performance are being increasingly used by music students to support their daily practice. The dominant piano performance evaluation models are based on metrics such as playing correct notes and global tempo. However, these metrics are often limited in capturing expressive aspects of performance, which can be seen through slight variations a performer chooses to employ in their playing. In order to capture some of these variations, we propose a web application that serves to compare the user's playing to that of professional recordings of the same piece. The users playing is plotted in real time on a tempovolume graph, alongside performances by great pianists such as Rubinstein and Horowitz. We then give this application to music students and from the feedback we receive, determine in what kind of live performance feedback will be useful to pianists

Color and Timbre Gestures: An Approach with Bicategories and Bigroupoids

White light can be decomposed into different colors, and a complex sound wave can be decomposed into its partials. While the physics behind transverse and longitudinal waves is quite different and several theories have been developed to investigate the complexity of colors and timbres, we can try to model their structural similarities through the language of categories. Then, we consider color mixing and color transition in painting, comparing them with timbre superposition and timbre morphing in orchestration and computer music in light of bicategories and bigroupoids. Colors and timbres can be a probe to investigate some relevant aspects of visual and auditory perception jointly with their connections. Thus, the use of categories proposed here aims to investigate color/timbre perception, influencing the computer science developments in this area