Measuring the Performance of Beat Tracking Algorithms Using a Beat Error Histogram

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The sound motion controller: a distributed system for interactive music performance

We developed an interactive system for music performance, able to control sound parameters in a responsive way with respect to the user’s movements. This system is conceived as a mobile application, provided with beat tracking and an expressive parameter modulation, interacting with motion sensors and effector units, which are connected to a music output, such as synthesizers or sound effects. We describe the various types of usage of our system and our achievements, aimed to increase the expression of music performance and provide an aid to music interaction. The results obtained outline a first level of integration and foresee future cognitive and technological research related to it

inTrack: High Precision Tracking of Mobile Sensor Nodes

Radio-interferometric ranging is a novel technique that allows for fine-grained node localization in networks of inexpensive COTS nodes. In this paper, we show that the approach can also be applied to precision tracking of mobile sensor nodes. We introduce inTrack, a cooperative tracking system based on radio-interferometry that features high accuracy, long range and low-power operation. The system utilizes a set of nodes placed at known locations to track a mobile sensor. We analyze how target speed and measurement errors affect the accuracy of the computed locations. To demonstrate the feasibility of our approach, we describe our prototype implementation using Berkeley motes. We evaluate the system using data from both simulations and field tests

Reliability-Informed Beat Tracking of Musical Signals

Abstract—A new probabilistic framework for beat tracking of musical audio is presented. The method estimates the time between consecutive beat events and exploits both beat and non-beat information by explicitly modeling non-beat states. In addition to the beat times, a measure of the expected accuracy of the estimated beats is provided. The quality of the observations used for beat tracking is measured and the reliability of the beats is automatically calculated. A k-nearest neighbor regression algorithm is proposed to predict the accuracy of the beat estimates. The performance of the beat tracking system is statistically evaluated using a database of 222 musical signals of various genres. We show that modeling non-beat states leads to a significant increase in performance. In addition, a large experiment where the parameters of the model are automatically learned has been completed. Results show that simple approximations for the parameters of the model can be used. Furthermore, the performance of the system is compared with existing algorithms. Finally, a new perspective for beat tracking evaluation is presented. We show how reliability information can be successfully used to increase the mean performance of the proposed algorithm and discuss how far automatic beat tracking is from human tapping. Index Terms—Beat-tracking, beat quality, beat-tracking reliability, k-nearest neighbor (k-NN) regression, music signal processing. I

Wing and body motion during flight initiation in Drosophila revealed by automated visual tracking

The fruit fly Drosophila melanogaster is a widely used model organism in studies of genetics, developmental biology and biomechanics. One limitation for exploiting Drosophila as a model system for behavioral neurobiology is that measuring body kinematics during behavior is labor intensive and subjective. In order to quantify flight kinematics during different types of maneuvers, we have developed a visual tracking system that estimates the posture of the fly from multiple calibrated cameras. An accurate geometric fly model is designed using unit quaternions to capture complex body and wing rotations, which are automatically fitted to the images in each time frame. Our approach works across a range of flight behaviors, while also being robust to common environmental clutter. The tracking system is used in this paper to compare wing and body motion during both voluntary and escape take-offs. Using our automated algorithms, we are able to measure stroke amplitude, geometric angle of attack and other parameters important to a mechanistic understanding of flapping flight. When compared with manual tracking methods, the algorithm estimates body position within 4.4±1.3% of the body length, while body orientation is measured within 6.5±1.9 deg. (roll), 3.2±1.3 deg. (pitch) and 3.4±1.6 deg. (yaw) on average across six videos. Similarly, stroke amplitude and deviation are estimated within 3.3 deg. and 2.1 deg., while angle of attack is typically measured within 8.8 deg. comparing against a human digitizer. Using our automated tracker, we analyzed a total of eight voluntary and two escape take-offs. These sequences show that Drosophila melanogaster do not utilize clap and fling during take-off and are able to modify their wing kinematics from one wingstroke to the next. Our approach should enable biomechanists and ethologists to process much larger datasets than possible at present and, therefore, accelerate insight into the mechanisms of free-flight maneuvers of flying insects

IDENTIFICATION OF COVER SONGS USING INFORMATION THEORETIC MEASURES OF SIMILARITY

13 pages, 5 figures, 4 tables. v3: Accepted version13 pages, 5 figures, 4 tables. v3: Accepted version13 pages, 5 figures, 4 tables. v3: Accepted versio

In - situ PMD Monitoring Using Coherent Detection and Polarization Tracking

Polarization mode dispersion (PMD) is a major impairment in high bit rate optical communication systems, causing system degradation. Although the random nature of PMD makes it difficult to be characterized, many measurement techniques have been developed to measure PMD and its effects on network reliability. However, the lack of in situ measurement techniques that can measure PMD on traffic carrying fibers has made it difficult for engineers to characterize the effects of PMD on wide bandwidth wavelength division multiplex (WDM) optical systems. The objective of this research is to develop an in situ PMD monitoring technique for long haul fiber optic links and use this technique to characterize the magnitude and distribution of PMD on these links. Towards this end, a systematic approach was followed to develop a monitoring equipment that can measure PMD on traffic carrying links. First, an earlier implementation of the PMD monitoring equipment based on coherent detection and polarization scrambling\cite{hui2007nbp} was improved in terms of size, speed and accuracy to make it more suitable for field measurements of PMD in traffic carrying fiber optic links. The coherent PMD monitor can measure differential group delay (DGD) values in the range of 0 to 50 ps. Secondly, using theoretical analysis, it was ascertained that the magnitude of PMD, the DGD measured by the PMD monitor, is the apparent DGD of the fiber and not its true DGD. Mathematical analysis was used to derive a relationship between the true DGD and the apparent DGD of the fiber. Also, it was found that the distribution of the apparent DGD is Rayleigh, unlike the true DGD which is Maxwellian. Thirdly, the hardware and software for implementing a polarization tracking algorithm to measure PMD was developed and tests were conducted to validate the algorithm in terms of speed, accuracy and the characteristics of the measured DGD. The polarization tracking algorithm has a higher measurement speed and lesser memory requirements than polarization scrambling. A number of laboratory experiments and field trials on traffic carrying fibers were conducted for a comparative analysis of polarization scrambling and polarization tracking. Using the polarization tracking algorithm to measure DGD, the measurement speed was found to be 20 times higher and the memory requirements about 80 times less than the memory required for DGD measurements using polarization scrambling. Results of the laboratory experiments and field trials agree with our theoretical analysis and the two algorithms have similar statistics for the measured DGD. Finally, the possibility of a more efficient implementation of polarization tracking was explored to measure PMD in real time. A run time implementation with the existing hardware and software was developed where the advantages of polarization tracking over polarization scrambling was made evident. The use of the in-situ PMD monitoring technique will enable network engineers to monitor the impact of PMD in live traffic carrying links and to select the wavelength bands that are relatively less affected by PMD

Automatic annotation of musical audio for interactive applications

PhDAs machines become more and more portable, and part of our everyday life, it becomes apparent that developing interactive and ubiquitous systems is an important aspect of new music applications created by the research community. We are interested in developing a robust layer for the automatic annotation of audio signals, to be used in various applications, from music search engines to interactive installations, and in various contexts, from embedded devices to audio content servers. We propose adaptations of existing signal processing techniques to a real time context. Amongst these annotation techniques, we concentrate on low and mid-level tasks such as onset detection, pitch tracking, tempo extraction and note modelling. We present a framework to extract these annotations and evaluate the performances of different algorithms. The first task is to detect onsets and offsets in audio streams within short latencies. The segmentation of audio streams into temporal objects enables various manipulation and analysis of metrical structure. Evaluation of different algorithms and their adaptation to real time are described. We then tackle the problem of fundamental frequency estimation, again trying to reduce both the delay and the computational cost. Different algorithms are implemented for real time and experimented on monophonic recordings and complex signals. Spectral analysis can be used to label the temporal segments; the estimation of higher level descriptions is approached. Techniques for modelling of note objects and localisation of beats are implemented and discussed. Applications of our framework include live and interactive music installations, and more generally tools for the composers and sound engineers. Speed optimisations may bring a significant improvement to various automated tasks, such as automatic classification and recommendation systems. We describe the design of our software solution, for our research purposes and in view of its integration within other systems.EU-FP6-IST-507142 project SIMAC (Semantic Interaction with Music Audio Contents); EPSRC grants GR/R54620; GR/S75802/01