title: Detecting overblown flute fingerings from the residual noise spectrum.
abstract: Producing a tone by increasing the blowing pressure to excite a higher frequency impedance minimum, or overblowing, is widely used in standard flute technique. In this paper, the effect of overblowing a fingering is explored with spectral analysis, and a fingering detector is designed based on acoustical knowledge and pattern classification techniques. The detector performs signal analysis of the strong broadband signal, that is, spectrally shaped by the pipe impedance, and measures the spectral energy during the attack around multiples of the fundamental frequency sub-multiples over the first octave and a half. It is trained and evaluated on sounds recorded with four expert performers. They played six series of tones from overblown and regular fingerings, with frequencies that are octave- and non-octave-related to the playing frequency. The best of the four proposed sound descriptors allows for a detection error below 1.3% for notes with two and three fingerings (C(5), D(5), C(6), and Cmusical sharp(6)) and below 14% for four (E(6)) or five fingerings (G(6)). The error is shown to dramatically increase when two fingerings' impedance become too similar (E(6) and A(4) and G(6) and C(5)).
authors.affiliation: Sound Processing and Control Laboratory, Input Devices and Music Interaction Laboratory, and Centre for Interdisciplinary Research in Music Media and Technology, Schulich School of Music of McGill University, Montreal, Quebec H3A 1E3, Canada. vincent@music.mcgill.ca
authors.forename: Vincent
authors.initials: V
authors.lastname: Verfaille
authors.forename: Philippe
authors.initials: P
authors.lastname: Depalle
authors.forename: Marcelo M
authors.initials: MM
authors.lastname: Wanderley
mesh_terms: D000162:Acoustics; D000328:Adult; D000399:Air Pressure; D000465:Algorithms; D016000:Cluster Analysis; D016002:Discriminant Analysis; D005385:Fingers; D006801:Humans; D009146:Music; D009622:Noise; D010363:Pattern Recognition, Automated / Q000379:methods; D025341:Principal Component Analysis; D011336:Probability; D011361:Professional Competence; D012815:Signal Processing, Computer-Assisted