DISCUSSION DU MÉCANISME DES RÉACTIONS DE TRANSFERT TRÈS INÉLASTIQUE

Sous ce terme sont englobées les réactions qui mettent en jeu des échanges importants de matière et d'énergie, sans aboutir à la fusion complète des partenaires. Lorsque le projectile utilisé est relativement léger (A < 40), on observe des réactions de transfert très inélastique dont les distributions angulaires dans le système du centre de masse correspondent à un produit léger émis préférentiellement vers l'avant, et pour des projectiles plus lourds, des réactions dites de quasi-fission dont les distributions angulaires présentent un maximum proche de l'angle d'effleurement. Les modèles théoriques utilisés pour rendre compte de ces réactions supposent l'intervention de forces de frottement (viscosité) entre les noyaux. Ces forces sont responsables des grandes pertes d'énergie cinétique observées. Le transfert de matière est traité comme un processus de diffusion en utilisant les équations de transfert issues de la mécanique statistique

LES PROGRAMMES EXPERIMENTAUX AUPRES DU SYNCHROCYCLOTRON D'ORSAY

Les programmes expérimentaux auprès du S.C. d'Orsay ont commencé il y a un an environ. L'accélérateur est une machine stable mais présentant quelques défauts de jeunesse. De nombreuses voies de recherches amorcées avec un certain succès sont décrites ci-dessous

A Monte-Carlo Method For Score Normalization in Automatic Speaker Verification Using Kullback-Leibler Distances

In this paper, we propose a new score normalization technique in Automatic Speaker Verification (ASV): the D-Norm. The main advantage of this score normalization is that it does not need any additional speech data nor external speaker population, as opposed to the state-ofthe-art approaches. The D-Norm is based on the use of Kullback-Leibler (KL) distances in an ASV context. In a first step, we estimate the KL distances with a Monte-Carlo method and we experimentally show that they are correlated with the verification scores. In a second step, we use this correlation to implement a score normalization procedure, the D-Norm. We analyse its performance and we compare it to that of a conventional normalization, the Z-Norm. The results show that performance of the D-Norm is comparable to that of the Z-Norm. We then conclude about the results we obtain and we discuss the applications of this work.

Supplementary material to the article: Estimating the structural segmentation of popular music pieces under regularity constraints

This document gathers descriptions of the structural segmentation systems considered in the IEEE/ACM TASLP paper by the same authors

Observation of coherent π0\pi^0 electroproduction on deuterons at large momentum transfer

The first experimental results for coherent $\pi^0$-electroproduction on the deuteron, $e+d\to e+d +\pi^0$, at large momentum transfer, are reported. The experiment was performed at Jefferson Laboratory at an incident electron energy of 4.05 GeV. A large pion production yield has been observed in a kinematical region for 1.1$<Q^2<$1.8 GeV$^2$, from threshold to 200 MeV excitation energy in the $d\pi^0$ system. The $Q^2$-dependence is compared with theoretical predictions.Comment: 26 page

Multiple pitch transcription using DBN-based musicological models

International audienceWe propose a novel approach to solve the problem of estimating pitches of notes present in an audio signal. We have developed a probabilistically rigorous model that takes into account temporal dependencies between musical notes and between the underlying chords, as well as the instantaneous dependencies between chords, notes and the observed note saliences. We investigated its modeling ability by measuring the cross-entropy with symbolic (MIDI) data and then proceed to observe the model's performance in multiple pitch estimation of audio data

Audio thumbnails for spoken content without transcription based on a maximum motif coverage criterion

International audienceThe paper presents a system to create audio thumbnails of spo- ken content, i.e., short audio summaries representative of the entire content, without resorting to a lexical representation. As an alternative to searching for relevant words and phrases in a transcript, unsupervised motif discovery is used to find short, word-like, repeating fragments at the signal level without acous- tic models. The output of the word discovery algorithm is ex- ploited via a maximum motif coverage criterion to generate a thumbnail in an extractive manner. A limited number of relevant segments are chosen within the data so as to include the maxi- mum number of motifs while remaining short enough and intel- ligible. Evaluation is performed on broadcast news reports with a panel of human listeners judging the quality of the thumb- nails. Results indicate that motif-based thumbnails stand be- tween random thumbnails and ASR-based keywords, however still far behind thumbnails and keywords humanly authored

Semiotic Description of Music Structure: an Introduction to the Quaero/Metiss Structural Annotations

12 pagesInternational audienceInterest has been steadily growing in semantic audio and music information retrieval for the description of music structure, i.e., the global organization of music pieces in terms of large-scale structural units. This article presents a detailed methodology for the semiotic description of music structure, based on concepts and criteria which are formulated as generically as possible. We sum up the essential principles and practices developed during an annotation effort deployed by our research group (Metiss) on audio data in the context of the Quaero project, which has led to the public release of over 380 annotations of pop songs from three different data sets. The paper also includes a few case studies and a concise statistical overview of the annotated data

Zero-resource audio-only spoken term detection based on a combination of template matching techniques

spoken term detection, template matching, unsupervised learning, posterior featuresInternational audienceSpoken term detection is a well-known information retrieval task that seeks to extract contentful information from audio by locating occurrences of known query words of interest. This paper describes a zero-resource approach to such task based on pattern matching of spoken term queries at the acoustic level. The template matching module comprises the cascade of a segmental variant of dynamic time warping and a self-similarity matrix comparison to further improve robustness to speech variability. This solution notably differs from more traditional train and test methods that, while shown to be very accurate, rely upon the availability of large amounts of linguistic resources. We evaluate our framework on different parameterizations of the speech templates: raw MFCC features and Gaussian posteriorgrams, French and English phonetic posteriorgrams output by two different state of the art phoneme recognizers