The PASCAL CHiME Speech Separation and Recognition Challenge

International audienceDistant microphone speech recognition systems that operate with humanlike robustness remain a distant goal. The key difficulty is that operating in everyday listening conditions entails processing a speech signal that is reverberantly mixed into a noise background composed of multiple competing sound sources. This paper describes a recent speech recognition evaluation that was designed to bring together researchers from multiple communities in order to foster novel approaches to this problem. The task was to identify keywords from sentences reverberantly mixed into audio backgrounds binaurally-recorded in a busy domestic environment. The challenge was designed to model the essential difficulties of multisource environment problem while remaining on a scale that would make it accessible to a wide audience. Compared to previous ASR evaluation a particular novelty of the task is that the utterances to be recognised were provided in a continuous audio background rather than as pre-segmented utterances thus allowing a range of background modelling techniques to be employed. The challenge attracted thirteen submissions. This paper describes the challenge problem, provides an overview of the systems that were entered and provides a comparison alongside both a baseline recognition system and human performance. The paper discusses insights gained from the challenge and lessons learnt for the design of future such evaluations

Murder She Wrote: Death and Drama in Nesting Woodpeckers

Woodpeckers serve as primary cavity excavators in fire-dominated forests. Secondary cavity users (SCU’s) rely heavily on cavities excavated by woodpeckers. Woodpecker species are declining, and some are now locally threatened. Management needs answers. How is woodpecker reproductive success impacted by the behavior of woodpeckers, SCU’s, and predators

No Time for Dead Time: Timing analysis of bright black hole binaries with NuSTAR

Timing of high-count rate sources with the NuSTAR Small Explorer Mission requires specialized analysis techniques. NuSTAR was primarily designed for spectroscopic observations of sources with relatively low count-rates rather than for timing analysis of bright objects. The instrumental dead time per event is relatively long (~2.5 msec), and varies by a few percent event-to-event. The most obvious effect is a distortion of the white noise level in the power density spectrum (PDS) that cannot be modeled easily with the standard techniques due to the variable nature of the dead time. In this paper, we show that it is possible to exploit the presence of two completely independent focal planes and use the cross power density spectrum to obtain a good proxy of the white noise-subtracted PDS. Thereafter, one can use a Monte Carlo approach to estimate the remaining effects of dead time, namely a frequency-dependent modulation of the variance and a frequency-independent drop of the sensitivity to variability. In this way, most of the standard timing analysis can be performed, albeit with a sacrifice in signal to noise relative to what would be achieved using more standard techniques. We apply this technique to NuSTAR observations of the black hole binaries GX 339-4, Cyg X-1 and GRS 1915+105.Comment: 13 pages, 8 figures, submitted to Ap

Some general properties of the renormalized stress-energy tensor for static quantum states on (n+1)-dimensional spherically symmetric black holes

We study the renormalized stress-energy tensor (RSET) for static quantum states on (n+1)-dimensional, static, spherically symmetric black holes. By solving the conservation equations, we are able to write the stress-energy tensor in terms of a single unknown function of the radial co-ordinate, plus two arbitrary constants. Conditions for the stress-energy tensor to be regular at event horizons (including the extremal and ``ultra-extremal'' cases) are then derived using generalized Kruskal-like co-ordinates. These results should be useful for future calculations of the RSET for static quantum states on spherically symmetric black hole geometries in any number of space-time dimensions.Comment: 9 pages, no figures, RevTeX4, references added, accepted for publication in General Relativity and Gravitatio

Tidal asteroseismology: Kepler's KOI-54

We develop a general framework for interpreting and analyzing high-precision lightcurves from eccentric stellar binaries. Although our methods are general, we focus on the recently discovered Kepler system KOI-54, a face-on binary of two A stars with $e=0.83$ and an orbital period of 42 days. KOI-54 exhibits strong ellipsoidal variability during its periastron passage; its lightcurve also contains ~20 pulsations at perfect harmonics of the orbital frequency, and another ~10 nonharmonic pulsations. Analysis of such data is a new form of asteroseismology in which oscillation amplitudes and phases rather than frequencies contain information that can be mined to constrain stellar properties. We qualitatively explain the physics of mode excitation and the range of harmonics expected to be observed. To quantitatively model observed pulsation spectra, we develop and apply a linear, tidally forced, nonadiabatic stellar oscillation formalism including the Coriolis force. We produce temporal power spectra for KOI-54 that are semi-quantitatively consistent with the observations. Both stars in the KOI-54 system are expected to be rotating pseudosynchronously, with resonant nonaxisymmetric modes providing a key contribution to the total torque; such resonances provide a possible explanation for the two largest-amplitude harmonic pulsations observed in KOI-54, although we find quantitative problems with this interpretation. We show in detail that the nonharmonic pulsations observed in KOI-54 can be produced by nonlinear three-mode coupling. The methods developed in this paper can be generalized in the future to determine the best-fit stellar parameters given pulsation data. We also derive an analytic model of KOI-54's ellipsoidal variability, including both tidal distortion and stellar irradiation, which can be used to model other similar systems.Comment: 26 pages, 9 figures. Accepted to MNRA

remote speech technology for speech professionals the cloudcast initiative

Clinical applications of speech technology face two challenges. The first is data sparsity. There is little data available to underpin techniques which are based on machine learning and, because it is difficult to collect disordered speech corpora, the only way to address this problem is by pooling what is produced from systems which are already in use. The second is personalisation. This field demands individual solutions, technology which adapts to its user rather than demanding that the user adapt to it. Here we introduce a project, CloudCAST, which addresses these two problems by making remote, adaptive technology available to professionals who work with speech: therapists, educators and clinicians. Index Terms: assistive technology, clinical applications of speech technolog