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Audio-based guitar tablature transcription using multipitch analysis and playability constraints
- in Proc. ICASSP
"... This paper proposes a method of guitar tablature transcription from audio signals. Multipitch estimation and fingering configuration estimation are essential for transcribing tablatures. Conventional multipitch estimation methods, including latent harmonic allocation (LHA), often estimate combinatio ..."
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This paper proposes a method of guitar tablature transcription from audio signals. Multipitch estimation and fingering configuration estimation are essential for transcribing tablatures. Conventional multipitch estimation methods, including latent harmonic allocation (LHA), often estimate combinations of pitches that people cannot play due to inherent physical constraints. Unplayable combina-tions of pitches are eliminated by filtering the results of LHA with three constraints. We first enumerate playable fingering configu-rations, and use them to suppress any undesirable combination of pitches. The optimal fingering configuration in each time frame is optimized to satisfy the need for temporal continuity by using dy-namic programming. We use synthesized guitar sounds from MIDI data (ground truth) for evaluation. Experiments with them demon-strate the improvement of multipitch estimation by 5.9 points on av-erage in F-measure and the transcribed tablatures are playable. Index Terms — guitar tablature, fingering configuration, multi-pitch estimation, onset detection, music signal processing 1.
Left and right-hand guitar playing techniques detection
"... In this paper we present a series of algorithms developed to detect the following guitar playing techniques: bend, hammer-on, pull-off, slide, palm muting and harmonic. Detection of playing techniques can be used to control external content (i.e audio loops and effects, videos, light events, etc.), ..."
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In this paper we present a series of algorithms developed to detect the following guitar playing techniques: bend, hammer-on, pull-off, slide, palm muting and harmonic. Detection of playing techniques can be used to control external content (i.e audio loops and effects, videos, light events, etc.), as well as to write real-time score or to assist guitar novices in their learning process. The guitar used is a Godin Multiac with an under-saddle RMC hexaphonic piezo pickup (one pickup per string, i.e six mono signals).
UNSUPERVISED TRAINING OF DETECTION THRESHOLD FOR POLYPHONIC MUSICAL NOTE TRACKING BASED ON EVENT PERIODICITY
"... A common approach to the detection of simultaneous musi-cal notes in an acoustic recording involves defining a function that yields activation levels for each candidate musical note over time. These levels tend to be high when the note is ac-tive and low when it is not. Therefore, by applying a simp ..."
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A common approach to the detection of simultaneous musi-cal notes in an acoustic recording involves defining a function that yields activation levels for each candidate musical note over time. These levels tend to be high when the note is ac-tive and low when it is not. Therefore, by applying a simple threshold decision process, it is possible to decide whether each note is active or not at a given time. Such a threshold, in general, is hard to set and has no physical meaning. In this paper, it is shown that the rhythmic characteristic of the mu-sical signal may be used to obtain a suitable threshold. The proposed method for obtaining the threshold is shown to have a greater generalization capability over different databases.
Automatic String Detection for Bass Guitar and Electric Guitar
"... Abstract. In this paper, we present a feature-based approach to au-tomatically estimate the string number in recordings of the bass guitar and the electric guitar. We perform different experiments to evaluate the classification performance on isolated note recordings. First, we analyze how factors s ..."
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Abstract. In this paper, we present a feature-based approach to au-tomatically estimate the string number in recordings of the bass guitar and the electric guitar. We perform different experiments to evaluate the classification performance on isolated note recordings. First, we analyze how factors such as the instrument, the playing style, and the pick-up settings affect the performance of the classification system. Second, we investigate, how the classification performance can be improved by re-jecting implausible classifications as well as aggregating the classification results over multiple adjacent time frames. The best results we obtained are f-measure values of F =.93 for the bass guitar (4 classes) and F =.90 for the electric guitar (6 classes).
AUTOMATIC TRANSCRIPTION OF GUITAR TABLATURE FROM AUDIO SIGNALS IN ACCORDANCEWITH PLAYER’S PROFICIENCY
"... We describe a method for automatically transcribing guitar tabla-tures from audio signals in accordance with the player’s proficiency for use as support for a guitar player’s practice. The system es-timates the multiple pitches in each time frame and the optimal fingering considering playability and ..."
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We describe a method for automatically transcribing guitar tabla-tures from audio signals in accordance with the player’s proficiency for use as support for a guitar player’s practice. The system es-timates the multiple pitches in each time frame and the optimal fingering considering playability and player’s proficiency. It com-bines a conventional multipitch estimation method with a basic dynamic programming method. The difficulty of the fingerings can be changed by tuning the parameter representing the relative weights of the acoustical reproducibility and the fingering easiness. Experi-ments conducted using synthesized guitar audio signals to evaluate the transcribed tablatures in terms of the multipitch estimation ac-curacy and fingering easiness demonstrated that the system can simplify the fingering with higher precision of multipitch estimation results than the conventional method. Index Terms — Dynamic programming (DP), guitar tablature transcription, multipitch estimation, music signal processing, per-formance proficiency. 1.
MULTIMODAL GUITAR: PERFORMANCE TOOLBOX AND STUDY WORKBENCH
"... All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Computational Models for Rhythm and Applications on Human-Machine Interactions
, 2013
"... gineering. Tese de doutorado apresentada a ̀ Faculdade de Engenharia Elétrica e de Computação da Universidade Es-tadual de Campinas como parte dos requisitos exigidos para a obtenção do t́ıtulo de Doutor em Engenharia Elétrica. Área de concentração: Engenharia de Computação. Orientador (S ..."
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gineering. Tese de doutorado apresentada a ̀ Faculdade de Engenharia Elétrica e de Computação da Universidade Es-tadual de Campinas como parte dos requisitos exigidos para a obtenção do t́ıtulo de Doutor em Engenharia Elétrica. Área de concentração: Engenharia de Computação. Orientador (Supervisor): Prof. Dr. Romis Ribeiro de Faissol
Project #03 Multimodal Guitar: Performance Toolbox and Study Workbench
"... Abstract—This project aims at studying how recent interactive and interaction technologies would help extend how we play the guitar, thus defining the “multimodal guitar”. We investigate two axes, 1) “A gestural/polyphonic sensing/processing toolbox to aug-ment guitar performances”, and 2) “An inter ..."
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Abstract—This project aims at studying how recent interactive and interaction technologies would help extend how we play the guitar, thus defining the “multimodal guitar”. We investigate two axes, 1) “A gestural/polyphonic sensing/processing toolbox to aug-ment guitar performances”, and 2) “An interactive guitar score following environment for adaptive learning”. These approaches share quite similar technological challenges (sensing, analysis, processing, synthesis and interaction methods) and dissemination intentions (community-based, low-cost, open-source whenever possible), while leading to different applications (respectively artistic and educational), still targeted towards experienced players and beginners. We designed and developed a toolbox for multimodal guitar performances containing the following tools: Polyphonic Pitch
