Bi-class classification of humpback whale sound units against complex background noise with Deep Convolution Neural Network

Automatically detecting sound units of humpback whales in complex time-varying background noises is a current challenge for scientists. In this paper, we explore the applicability of Convolution Neural Network (CNN) method for this task. In the evaluation stage, we present 6 bi-class classification experimentations of whale sound detection against different background noise types (e.g., rain, wind). In comparison to classical FFT-based representation like spectrograms, we showed that the use of image-based pretrained CNN features brought higher performance to classify whale sounds and background noise.Comment: arXiv admin note: text overlap with arXiv:1702.02741 by other author

A Revaluation of Learning Practices in Indian Classical Music Using Technological Tools

Each khyāl performance of Indian classical music is unique and unreproducible because it is mainly based on improvisation. As for most orally transmitted musical repertoires, learning practices are essential as they guarantee that the musical codes are properly reproduced from one generation to another. In Indian classical music, practice, tightly imbricated in the pupil – teacher relation, favors clearly the imitation. Students tend to reproduce more or less successfully their master’s style. That’s why in order to be creative, it is necessary that each musician develops his own skills of understanding, experimentation and invention. Today, technological tools have considerably transformed our way of learning. From now on, it is possible to have access to considerable data for the understanding of traditional music, and to listen, record and analyse them via numerous audio softwares. Indeed, works by visualization allows reporting knowhow common to all these musics (fingering, musical process, improvisation, patterns…). Through various softwares and practice examples from Rajam’s dynasty (hindustani violinist players), hindustani violin lessons and rāg performances, we will present a “toolbox” useful for all musicians and musicologist to improve their self-study. If the pedagogy and teaching can give us comprehension keys, the apprenticeship, such as it is practiced in North India and in the long master to pupil’s tradition, favors clearly the imitation at the expanse of the assimilation. The pupil learns above all by imitation and by impregnation, without taking the time to understand or to write. He learns to know a number of ingredients, but does not inevitably learn how to use it. In this way, the pupil tends inexorably to reproduce with varying degrees of acuteness the master’s style. His space of creativity is extremely reduced even non-existent. The musician will feel difficulties finding his own style. For that purpose, it is necessary to him to be able to stand back, to be able to experiment, invent and understand. The technological tools really transformed our way of learning in our daily practice. So the analysis via a number of IT data and software allows to understand and to learn musical processes, specific ornamentations, rarely taught. In addition, it is possible to question the relationship between what is taught by the master and what is produced on stage. Through the comparison of different performances, different performers and different learning lessons, one can clearly dissociates the stored material from the improvised material, i.e. the fixed components from the modular elements. This current work aims to study this question, focusing on different rāg according to the vocal tradition of khyāl within the Rajam’s Dynasty, violinist descendants. In this communication, we investigate the possibility of using modern computer-based technologies as a teaching assistance system for Indian classical music. Due to its improvisation nature, a comparative approach is necessary to analyse it. For example, by comparing recordings between Hindustani violin lessons at the Hubli- Gurukul (India, August 2010-2012) and Hindustani rāg performances, it is possible to show up the way(s) Rajam Dynasty musicians transform the structural and structuring1 elements of a rāg. At a larger scale of analysis, by multiplying the interpreters on a same rāg, we could quantitatively compare their different improvisation strategies, and better understanding the fundamental elements of a rāg that need to be properly taught to every musician

A search for passive protoplanetary disks in the Taurus-Auriga star-forming region

We conducted a 12-month monitoring campaign of 33 T Tauri stars (TTS) in Taurus. Our goal was to monitor objects that possess a disk but have a weak Halpha line, a common accretion tracer for young stars, to determine whether they host a passive circumstellar disk. We used medium-resolution optical spectroscopy to assess the objects' accretion status and to measure the Halpha line. We found no convincing example of passive disks; only transition disk and debris disk systems in our sample are non-accreting. Among accretors, we find no example of flickering accretion, leading to an upper limit of 2.2% on the duty cycle of accretion gaps assuming that all accreting TTS experience such events. Combining literature results with our observations, we find that the reliability of traditional Halpha-based criteria to test for accretion is high but imperfect, particularly for low-mass TTS. We find a significant correlation between stellar mass and the full width at 10 per cent of the peak (W10%) of the Halpha line that does not seem to be related to variations in free-fall velocity. Finally, our data reveal a positive correlation between the Halpha equivalent width and its W10%, indicative of a systematic modulation in the line profile whereby the high-velocity wings of the line are proportionally more enhanced than its core when the line luminosity increases. We argue that this supports the hypothesis that the mass accretion rate on the central star is correlated with the Halpha W10% through a common physical mechanism.Comment: accepted for publication in MNRAS; 26 pages, 9 figures, 3 table

Unveiling the atmospheres of giant exoplanets with an EChO-class mission

More than a thousand exoplanets have been discovered over the last decade. Perhaps more excitingly, probing their atmospheres has become possible. With current data we have glimpsed the diversity of exoplanet atmospheres that will be revealed over the coming decade. However, numerous questions concerning their chemical composition, thermal structure, and atmospheric dynamics remain to be answered. More observations of higher quality are needed. In the next years, the selection of a space-based mission dedicated to the spectroscopic characterization of exoplanets would revolutionize our understanding of the physics of planetary atmospheres. Such a mission was proposed to the ESA cosmic vision program in 2014. Our paper is therefore based on the planned capabilities of the Exoplanet Characterization Observatory (EChO), but it should equally apply to any future mission with similar characteristics. With its large spectral coverage (0.4 − 16 μm), high spectral resolution (λ/Δλ > 300 below 5 μm and λ/Δλ > 30 above 5 μm) and 1.5m mirror, a future mission such as EChO will provide spectrally resolved transit lightcurves, secondary eclipses lightcurves, and full phase curves of numerous exoplanets with an unprecedented signal-to-noise ratio. In this paper, we review some of today’s main scientific questions about gas giant exoplanets atmospheres, for which a future mission such as EChO will bring a decisive contribution