X_System

The X_System makes the playing, writing, and learning of music – even when using unconventional tunings – more intuitive, more logical, more expressive, and better sounding. The X_System allows for: • different temperaments to be chosen at the flick of a switch; • tunings to be dynamically altered at the push of a lever; • the use of a special hexagonal button-field that allows for any given interval or chord always to have the same shape on that button-field; • consonant chords to have their consonance maximised, whatever the tuning actually chosen; • radical changes to be made to the timbral character of tones using a minimal number of controls; • a choice of keyboard mappings, which enable for the balance between number of intervals and octaves to be altered

Video Logo Retrieval based on local Features

Estimation of the frequency and duration of logos in videos is important and challenging in the advertisement industry as a way of estimating the impact of ad purchases. Since logos occupy only a small area in the videos, the popular methods of image retrieval could fail. This paper develops an algorithm called Video Logo Retrieval (VLR), which is an image-to-video retrieval algorithm based on the spatial distribution of local image descriptors that measure the distance between the query image (the logo) and a collection of video images. VLR uses local features to overcome the weakness of global feature-based models such as convolutional neural networks (CNN). Meanwhile, VLR is flexible and does not require training after setting some hyper-parameters. The performance of VLR is evaluated on two challenging open benchmark tasks (SoccerNet and Standford I2V), and compared with other state-of-the-art logo retrieval or detection algorithms. Overall, VLR shows significantly higher accuracy compared with the existing methods.Comment: Accepted by ICIP 20. Contact author: Bochen Guan ([email protected]

Metrics for pitch collections

Models of the perceived distance between pairs of pitch collections are a core component of broader models of the perception of tonality as a whole. Numerous different distance measures have been proposed, including voice-leading, psychoacoustic, and pitch and interval class distances; but, so far, there has been no attempt to bind these different measures into a single mathematical framework, nor to incorporate the uncertain or probabilistic nature of pitch perception (whereby tones with similar frequencies may, or may not, be heard as having the same pitch). To achieve these aims, we embed pitch collections in novel multi-way expectation arrays, and show how metrics between such arrays can model the perceived dissimilarity of the pitch collections they embed. By modeling the uncertainties of human pitch perception, expectation arrays indicate the expected number of tones, ordered pairs of tones, ordered triples of tones and so forth, that are heard as having any given pitch, dyad of pitches, triad of pitches, and so forth. The pitches can be either absolute or relative (in which case the arrays are invariant with respect to transposition). We provide a number of examples that show how the metrics accord well with musical intuition, and suggest some ways in which this work may be developed

EXPERIMENTS ON THE RELATIONSHIP BETWEEN PERDE AND SEYIR IN TURKISH MAKAM MUSIC

"WHEN I WAS A KID, THE ELDERS IN THE VILLAGE COULD TELL THE MAKAM OF A PIECE JUST BY LISTENING." While interviewing performers, enthusiasts, and experts in traditional Turkish taksims (improvisations), variations of this comment were made many times. Some of the respondents claimed to be able to identify the makam of a taksim, but others believed that this ability might now be a lost art. This paper documents a series of experiments (based on caricaturized or skeletonized taksim-like creations) designed to determine if it is possible to identify the makam from purely acoustical features, and, when possible, to determine the relative importance of the various audible features that may be used to establish the makam. Two basic classes of features are investigated: perde (the set of pitches used in the performance) and seyir (which relates to temporal motion within the piece, for instance, repetitive or common motives or melodic contour). The experiments provide evidence that both kinds of features contribute to the ability to recognize makams. Experiments that randomize the order of events show that pitch cues (perde) are often adequate to allow accurate identification of the makam. In experiments where both pitch and temporal cues are present but conflict (for example, a piece in which the perde is chosen from one makam and the seyir from another), experts often favor the temporal information