Detecting Episodes with Harmonic Sequences for Fugue Analysis

International audienceFugues alternate between instances of the subject and of other patterns, such as the counter-subject, and modulatory sections called episodes. The episodes play an important role in the overall design of a fugue: detecting them may help the analysis of the fugue, in complement to a subject and a counter-subject detection. We propose an algorithm to retrieve episodes in the fugues of the first book of Bach's Well-Tempered Clavier, starting from a symbolic score which is already track-separated. The algorithm does not use any information on subject or counter-subject occurrences, but tries to detect partial harmonic sequences, that is similar pitch contour in at least two voices. For this, it uses a substitution function considering "quantized partially overlapping intervals" [Lemström and Laine, 98] and a strict length matching for all notes, except for the first and the last one. On half of the tested fugues, the algorithm has correct or good results, enabling to sketch the design of the fugue

The Variable Markov Oracle: Algorithms for Human Gesture Applications

This article introduces the Variable Markov Oracle (VMO) data structure for multivariate time series indexing. VMO can identify repetitive fragments and find sequential similarities between observations. VMO can also be viewed as a combination of online clustering algorithms with variable-order Markov constraints. The authors use VMO for gesture query-by-content and gesture following. A probabilistic interpretation of the VMO query-matching algorithm is proposed to find an analogy to the inference problem in a hidden Markov model (HMM). This probabilistic interpretation extends VMO to be not only a data structure but also a model for time series. Query-by-content experiments were conducted on a gesture database that was recorded using a Kinect 3D camera, showing state-of-the-art performance. The query-by-content experiments' results are compared to previous works using HMM and dynamic time warping. Gesture following is described in the context of an interactive dance environment that aims to integrate human movements with computer-generated graphics to create an augmented reality performance

Loop-aware Audio Recording for the Web

Music loops are audio recordings used as basic building blocks in many types of music. The use of pre-recorded loops facilitates engagement into music creation to users regardless of their background in music theory. Using online loop databases also affords simple collaboration and exchange. Hence, music loops are particularly attractive for web audio applications. However, traditional musical audio recording typically relies on complex DAW software. Recording loops usually requires consideration of musical meter and tempo, and withstanding metronome sounds. In this paper, we propose loop-aware audio recording as a use case for web audio technologies. Our approach supports hands-free, low-stress recording of music loops in web- enabled devices. The system is able to detect repetitions in an incoming audio stream. Based on this information, it segments and ranks the repeated fragments, presenting the list to the user. We provide an example implementation, and evaluate the use of the different MIR libraries available in the web audio platform for the proposed task