Fuzzy Theory-based Air Valve Control for Auto-Score-Recognition Soprano Recorder Machines
- 10.2991/jrnal.k.211108.010How to use a DOI?
- Auto-score-recognition soprano recorder machines (ASRSRM); LabVIEW; Arduino; fuzzy theory-based air valve control; pneumatic cylinder
In the past research, there are many disadvantages to score recognition and flute performance. In view of this, we will improve the above disadvantages in this article. First, for the music score recognition, a y-axis projection method is used to detect the staff position and eliminate it to replace the erosion and expansion in morphology. This feature can be used to distinguish the notes, which have a specific writing style on the staff. For the soprano recorder playing, in the past we used finger-shaped electric arms to press the blow hole to cause that the speed of the score cannot be kept up. To improve this drawback, the motor is changed to a solenoid valve to facilitate the pneumatic cylinder to smoothly press the blow hole. In addition, since the difference in pitch of the soprano recorder requires different air pressure, we increase one valve to three valves. Moreover, the range is divided into bass, midrange, and treble. Not only that, fuzzy theory-based air valve control is applied to auto-score-recognition soprano recorder machines to greatly improve the sound distortion caused by the original single air valve. Experiments prove that the fuzzy theory-based air valve control combined with sheet music recognition techniques can fully realize the functions of autoplaying soprano recorder machines.
- © 2021 The Author. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
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TY - JOUR AU - Chun-Chieh Wang PY - 2021 DA - 2021/12/27 TI - Fuzzy Theory-based Air Valve Control for Auto-Score-Recognition Soprano Recorder Machines JO - Journal of Robotics, Networking and Artificial Life SP - 278 EP - 283 VL - 8 IS - 4 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.k.211108.010 DO - 10.2991/jrnal.k.211108.010 ID - Wang2021 ER -