Pattern formation in directional solidification under shear flow. I: Linear stability analysis and basic patterns

An asymptotic interface equation for directional solidification near the absolute stabiliy limit is extended by a nonlocal term describing a shear flow parallel to the interface. In the long-wave limit considered, the flow acts destabilizing on a planar interface. Moreover, linear stability analysis suggests that the morphology diagram is modified by the flow near the onset of the Mullins-Sekerka instability. Via numerical analysis, the bifurcation structure of the system is shown to change. Besides the known hexagonal cells, structures consisting of stripes arise. Due to its symmetry-breaking properties, the flow term induces a lateral drift of the whole pattern, once the instability has become active. The drift velocity is measured numerically and described analytically in the framework of a linear analysis. At large flow strength, the linear description breaks down, which is accompanied by a transition to flow-dominated morphologies, described in a companion paper. Small and intermediate flows lead to increased order in the lattice structure of the pattern, facilitating the elimination of defects. Locally oscillating structures appear closer to the instability threshold with flow than without.Comment: 20 pages, Latex, accepted for Physical Review

A Comparison of Temporal Response Function Estimation Methods for Auditory Attention Decoding

The decoding of selective auditory attention from noninvasive electroencephalogram (EEG) data is of interest in brain computer interface and auditory perception research. The current state-of-the-art approaches for decoding the attentional selection of listeners are based on temporal response functions (TRFs). In the current context, a TRF is a function that facilitates a mapping between features of sound streams and EEG responses. It has been shown that when the envelope of attended speech and EEG responses are used to derive TRF mapping functions, the TRF model predictions can be used to discriminate between attended and unattended talkers. However, the predictive performance of the TRF models is dependent on how the TRF model parameters are estimated. There exist a number of TRF estimation methods that have been published, along with a variety of datasets. It is currently unclear if any of these methods perform better than others, as they have not yet been compared side by side on a single standardized dataset in a controlled fashion. Here, we present a comparative study of the ability of different TRF estimation methods to classify attended speakers from multi-channel EEG data. The performance of the TRF estimation methods is evaluated using different performance metrics on a set of labeled EEG data from 18 subjects listening to mixtures of two speech streams

Science and Film-making

The essay reviews the literature, mostly historical, on the relationship between science and film-making, with a focus on the science documentary. It then discusses the circumstances of the emergence of the wildlife making-of documentary genre. The thesis examined here is that since the early days of cinema, film-making has evolved from being subordinate to science, to being an equal partner in the production of knowledge, controlled by non-scientists

Multiple-instrument polyphonic music transcription using a temporally constrained shift-invariant model

A method for automatic transcription of polyphonic music is proposed in this work that models the temporal evolution of musical tones. The model extends the shift-invariant probabilistic latent component analysis method by supporting the use of spectral templates that correspond to sound states such as attack, sustain, and decay. The order of these templates is controlled using hidden Markov model-based temporal constraints. In addition, the model can exploit multiple templates per pitch and instrument source. The shift-invariant aspect of the model makes it suitable for music signals that exhibit frequency modulations or tuning changes. Pitch-wise hidden Markov models are also utilized in a postprocessing step for note tracking. For training, sound state templates were extracted for various orchestral instruments using isolated note samples. The proposed transcription system was tested on multiple-instrument recordings from various datasets. Experimental results show that the proposed model is superior to a non-temporally constrained model and also outperforms various state-of-the-art transcription systems for the same experiment

Neuromagnetic Evidence for Early Auditory Restoration of Fundamental Pitch

Background: Understanding the time course of how listeners reconstruct a missing fundamental component in an auditory stimulus remains elusive. We report MEG evidence that the missing fundamental component of a complex auditory stimulus is recovered in auditory cortex within 100 ms post stimulus onset. Methodology: Two outside tones of four-tone complex stimuli were held constant (1200 Hz and 2400 Hz), while two inside tones were systematically modulated (between 1300 Hz and 2300 Hz), such that the restored fundamental (also knows as ‘‘virtual pitch’’) changed from 100 Hz to 600 Hz. Constructing the auditory stimuli in this manner controls for a number of spectral properties known to modulate the neuromagnetic signal. The tone complex stimuli only diverged on the value of the missing fundamental component. Principal Findings: We compared the M100 latencies of these tone complexes to the M100 latencies elicited by their respective pure tone (spectral pitch) counterparts. The M100 latencies for the tone complexes matched their pure sinusoid counterparts, while also replicating the M100 temporal latency response curve found in previous studies. Conclusions: Our findings suggest that listeners are reconstructing the inferred pitch by roughly 100 ms after stimulus onset and are consistent with previous electrophysiological research suggesting that the inferential pitch is perceived i

Across-Channel Timing Differences as a Potential Code for the Frequency of Pure Tones

When a pure tone or low-numbered harmonic is presented to a listener, the resulting travelling wave in the cochlea slows down at the portion of the basilar membrane (BM) tuned to the input frequency due to the filtering properties of the BM. This slowing is reflected in the phase of the response of neurons across the auditory nerve (AN) array. It has been suggested that the auditory system exploits these across-channel timing differences to encode the pitch of both pure tones and resolved harmonics in complex tones. Here, we report a quantitative analysis of previously published data on the response of guinea pig AN fibres, of a range of characteristic frequencies, to pure tones of different frequencies and levels. We conclude that although the use of across-channel timing cues provides an a priori attractive and plausible means of encoding pitch, many of the most obvious metrics for using that cue produce pitch estimates that are strongly influenced by the overall level and therefore are unlikely to provide a straightforward means for encoding the pitch of pure tones

Understanding Pitch Perception as a Hierarchical Process with Top-Down Modulation

Pitch is one of the most important features of natural sounds, underlying the perception of melody in music and prosody in speech. However, the temporal dynamics of pitch processing are still poorly understood. Previous studies suggest that the auditory system uses a wide range of time scales to integrate pitch-related information and that the effective integration time is both task- and stimulus-dependent. None of the existing models of pitch processing can account for such task- and stimulus-dependent variations in processing time scales. This study presents an idealized neurocomputational model, which provides a unified account of the multiple time scales observed in pitch perception. The model is evaluated using a range of perceptual studies, which have not previously been accounted for by a single model, and new results from a neurophysiological experiment. In contrast to other approaches, the current model contains a hierarchy of integration stages and uses feedback to adapt the effective time scales of processing at each stage in response to changes in the input stimulus. The model has features in common with a hierarchical generative process and suggests a key role for efferent connections from central to sub-cortical areas in controlling the temporal dynamics of pitch processing

Automatic transcription of Turkish microtonal music

Automatic music transcription, a central topic in music signal analysis, is typically limited to equal-tempered music and evaluated on a quartertone tolerance level. A system is proposed to automatically transcribe microtonal and heterophonic music as applied to the makam music of Turkey. Specific traits of this music that deviate from properties targeted by current transcription tools are discussed, and a collection of instrumental and vocal recordings is compiled, along with aligned microtonal reference pitch annotations. An existing multi-pitch detection algorithm is adapted for transcribing music with 20 cent resolution, and a method for converting a multi-pitch heterophonic output into a single melodic line is proposed. Evaluation metrics for transcribing microtonal music are applied, which use various levels of tolerance for inaccuracies with respect to frequency and time. Results show that the system is able to transcribe microtonal instrumental music at 20 cent resolution with an F-measure of 56.7%, outperforming state-of-the-art methods for the same task. Case studies on transcribed recordings are provided, to demonstrate the shortcomings and the strengths of the proposed method.QC 20161031</p