Good vibrations: Guiding body movements with vibrotactile feedback

We describe the ongoing development of a system to support the teaching of good posture and bowing technique to novice violin players. Using an inertial motion capture system we can track in real-time a player’s bowing action and how it deviates from a target trajectory set by their music teacher. The system provides real-time vibrotactile feedback on the correctness of the student’s posture and bowing action. We present the findings of an initial study that shows that vibrotactile feedback can guide arm movements in one and two dimension pointing tasks. The advantages of vibrotactile feedback for teaching basic bowing technique to novice violin players are that it does not place demands on the students’ visual and auditory systems which are already heavily involved in the activity of music making, and is understood with little training

Towards a real-time system for teaching novices good violin bowing technique

We describe the ongoing development of a system to support the teaching of good posture and bowing technique to novice violin players. Using an inertial motion capture system we can track in real-time: i) a player’s bowing action (and measure how it deviates from a target trajectory); ii) whether the player is holding their violin correctly. We detail some initial experiments that show that vibrotactile feedback can guide arm movements in one and two dimensions. We then present some preliminary findings from integrating the motion capture and feedback components into a prototype real-time training system. The advantages of vibrotactile feedback are that: i) it does not use the students’ visual and auditory systems which are already involved in the activity of music making; ii) it is an intuitive way to guide body movements

SMA Technical Report

Technical report from pilot studies in the Sensing Music-related Actions group. The report presents simple motion sensor technology and issues regarding pre-processing of music-related motion data. In cognitive music research, ones main focus is the relationship between music and human beings. This involves emotions, moods, perception, expression, interaction with other people, interaction with musical instruments and other interfaces, among many other things. Due to the nature of music as a subjective experience, verbal utterances on these aspects tend to be coloured by the person who makes them. Such utterances are limited by the vocabulary of the person, and by the process of consciously transforming these inner feelings and experiences to words (Leman 2007: 5f). Thus, gesture research has become extensively popular among researchers wanting a deeper understanding of how people interact with music. In this kind of research, several different methods are used, using for example infrared-sensitive cameras (Wiesendanger et al. 2006) or video recordings in combination with MIDI (Jabusch 2006). This paper presents methods being used in a pilot study for the Sensing Music-related Actions project at the Department of Musicology and the Department of Informatics at the University of Oslo. Here I will discuss the methods for apprehending and analysing gestural data in this project, especially looking into use of sensors for measuring movement and tracking absolute position. In this project, a superior goal is to develop methods for studying gestures in musical performance. In a large view this involves gathering data, analysing the data and organizing the data in such a way that we ourselves and others easily can find and understand the data

The digitally 'Hand Made' object

This article will outline the author’s investigations of types of computer interfaces in practical three-dimensional design practice. The paper contains a description of two main projects in glass and ceramic tableware design, using a Microscribe G2L digitising arm as an interface to record three-dimensional spatial\ud design input.\ud \ud The article will provide critical reflections on the results of the investigations and will argue that new approaches in digital design interfaces could have relevance in developing design methods which incorporate more physical ‘human’ expressions in a three-dimensional design practice. The research builds on concepts indentified in traditional craft practice as foundations for constructing new types of creative practices based on the use of digital technologies, as outlined by McCullough (1996)

AXMEDIS 2007 Conference Proceedings

The AXMEDIS International Conference series has been established since 2005 and is focused on the research, developments and applications in the cross-media domain, exploring innovative technologies to meet the challenges of the sector. AXMEDIS2007 deals with all subjects and topics related to cross-media and digital-media content production, processing, management, standards, representation, sharing, interoperability, protection and rights management. It addresses the latest developments and future trends of the technologies and their applications, their impact and exploitation within academic, business and industrial communities

Automatic Transcription of Bass Guitar Tracks applied for Music Genre Classification and Sound Synthesis

Musiksignale bestehen in der Regel aus einer Überlagerung mehrerer Einzelinstrumente. Die meisten existierenden Algorithmen zur automatischen Transkription und Analyse von Musikaufnahmen im Forschungsfeld des Music Information Retrieval (MIR) versuchen, semantische Information direkt aus diesen gemischten Signalen zu extrahieren. In den letzten Jahren wurde häufig beobachtet, dass die Leistungsfähigkeit dieser Algorithmen durch die Signalüberlagerungen und den daraus resultierenden Informationsverlust generell limitiert ist. Ein möglicher Lösungsansatz besteht darin, mittels Verfahren der Quellentrennung die beteiligten Instrumente vor der Analyse klanglich zu isolieren. Die Leistungsfähigkeit dieser Algorithmen ist zum aktuellen Stand der Technik jedoch nicht immer ausreichend, um eine sehr gute Trennung der Einzelquellen zu ermöglichen. In dieser Arbeit werden daher ausschließlich isolierte Instrumentalaufnahmen untersucht, die klanglich nicht von anderen Instrumenten überlagert sind. Exemplarisch werden anhand der elektrischen Bassgitarre auf die Klangerzeugung dieses Instrumentes hin spezialisierte Analyse- und Klangsynthesealgorithmen entwickelt und evaluiert.Im ersten Teil der vorliegenden Arbeit wird ein Algorithmus vorgestellt, der eine automatische Transkription von Bassgitarrenaufnahmen durchführt. Dabei wird das Audiosignal durch verschiedene Klangereignisse beschrieben, welche den gespielten Noten auf dem Instrument entsprechen. Neben den üblichen Notenparametern Anfang, Dauer, Lautstärke und Tonhöhe werden dabei auch instrumentenspezifische Parameter wie die verwendeten Spieltechniken sowie die Saiten- und Bundlage auf dem Instrument automatisch extrahiert. Evaluationsexperimente anhand zweier neu erstellter Audiodatensätze belegen, dass der vorgestellte Transkriptionsalgorithmus auf einem Datensatz von realistischen Bassgitarrenaufnahmen eine höhere Erkennungsgenauigkeit erreichen kann als drei existierende Algorithmen aus dem Stand der Technik. Die Schätzung der instrumentenspezifischen Parameter kann insbesondere für isolierte Einzelnoten mit einer hohen Güte durchgeführt werden.Im zweiten Teil der Arbeit wird untersucht, wie aus einer Notendarstellung typischer sich wieder- holender Basslinien auf das Musikgenre geschlossen werden kann. Dabei werden Audiomerkmale extrahiert, welche verschiedene tonale, rhythmische, und strukturelle Eigenschaften von Basslinien quantitativ beschreiben. Mit Hilfe eines neu erstellten Datensatzes von 520 typischen Basslinien aus 13 verschiedenen Musikgenres wurden drei verschiedene Ansätze für die automatische Genreklassifikation verglichen. Dabei zeigte sich, dass mit Hilfe eines regelbasierten Klassifikationsverfahrens nur Anhand der Analyse der Basslinie eines Musikstückes bereits eine mittlere Erkennungsrate von 64,8 % erreicht werden konnte.Die Re-synthese der originalen Bassspuren basierend auf den extrahierten Notenparametern wird im dritten Teil der Arbeit untersucht. Dabei wird ein neuer Audiosynthesealgorithmus vorgestellt, der basierend auf dem Prinzip des Physical Modeling verschiedene Aspekte der für die Bassgitarre charakteristische Klangerzeugung wie Saitenanregung, Dämpfung, Kollision zwischen Saite und Bund sowie dem Tonabnehmerverhalten nachbildet. Weiterhin wird ein parametrischerAudiokodierungsansatz diskutiert, der es erlaubt, Bassgitarrenspuren nur anhand der ermittel- ten notenweisen Parameter zu übertragen um sie auf Dekoderseite wieder zu resynthetisieren. Die Ergebnisse mehrerer Hötest belegen, dass der vorgeschlagene Synthesealgorithmus eine Re- Synthese von Bassgitarrenaufnahmen mit einer besseren Klangqualität ermöglicht als die Übertragung der Audiodaten mit existierenden Audiokodierungsverfahren, die auf sehr geringe Bitraten ein gestellt sind.Music recordings most often consist of multiple instrument signals, which overlap in time and frequency. In the field of Music Information Retrieval (MIR), existing algorithms for the automatic transcription and analysis of music recordings aim to extract semantic information from mixed audio signals. In the last years, it was frequently observed that the algorithm performance is limited due to the signal interference and the resulting loss of information. One common approach to solve this problem is to first apply source separation algorithms to isolate the present musical instrument signals before analyzing them individually. The performance of source separation algorithms strongly depends on the number of instruments as well as on the amount of spectral overlap.In this thesis, isolated instrumental tracks are analyzed in order to circumvent the challenges of source separation. Instead, the focus is on the development of instrument-centered signal processing algorithms for music transcription, musical analysis, as well as sound synthesis. The electric bass guitar is chosen as an example instrument. Its sound production principles are closely investigated and considered in the algorithmic design.In the first part of this thesis, an automatic music transcription algorithm for electric bass guitar recordings will be presented. The audio signal is interpreted as a sequence of sound events, which are described by various parameters. In addition to the conventionally used score-level parameters note onset, duration, loudness, and pitch, instrument-specific parameters such as the applied instrument playing techniques and the geometric position on the instrument fretboard will be extracted. Different evaluation experiments confirmed that the proposed transcription algorithm outperformed three state-of-the-art bass transcription algorithms for the transcription of realistic bass guitar recordings. The estimation of the instrument-level parameters works with high accuracy, in particular for isolated note samples.In the second part of the thesis, it will be investigated, whether the sole analysis of the bassline of a music piece allows to automatically classify its music genre. Different score-based audio features will be proposed that allow to quantify tonal, rhythmic, and structural properties of basslines. Based on a novel data set of 520 bassline transcriptions from 13 different music genres, three approaches for music genre classification were compared. A rule-based classification system could achieve a mean class accuracy of 64.8 % by only taking features into account that were extracted from the bassline of a music piece.The re-synthesis of a bass guitar recordings using the previously extracted note parameters will be studied in the third part of this thesis. Based on the physical modeling of string instruments, a novel sound synthesis algorithm tailored to the electric bass guitar will be presented. The algorithm mimics different aspects of the instrument’s sound production mechanism such as string excitement, string damping, string-fret collision, and the influence of the electro-magnetic pickup. Furthermore, a parametric audio coding approach will be discussed that allows to encode and transmit bass guitar tracks with a significantly smaller bit rate than conventional audio coding algorithms do. The results of different listening tests confirmed that a higher perceptual quality can be achieved if the original bass guitar recordings are encoded and re-synthesized using the proposed parametric audio codec instead of being encoded using conventional audio codecs at very low bit rate settings