Proceedings of the 2018 3rd International Conference on Communications, Information Management and Network Security (CIMNS 2018)

A Frame-Based Extended MIDI-Pitch Detection Algorithm Based on Variable Sampling Technology

Authors
Yin Feng, Mingtai Lin
Corresponding Author
Yin Feng
Available Online November 2018.
DOI
10.2991/cimns-18.2018.7How to use a DOI?
Keywords
extended MIDI pitch; singing transcription; singing signal processing
Abstract

This paper proposes a framed-based extended MIDI-pitch detection algorithm based on variable sampling technology. Symbols P--, P-, P+ and P++ are used to present four different logarithmic frequencies around the MIDI pitch P (integer) within 100 cents interval and called as extended MIDI-pitch to enhance the expression resolution of MIDI pitch of a signal frame. Experiment shows that the algorithm has a good raw pitch accuracy rate and less computation complexity o(nlog2n).

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 3rd International Conference on Communications, Information Management and Network Security (CIMNS 2018)
Series
Advances in Computer Science Research
Publication Date
November 2018
ISBN
978-94-6252-620-4
ISSN
2352-538X
DOI
10.2991/cimns-18.2018.7How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yin Feng
AU  - Mingtai Lin
PY  - 2018/11
DA  - 2018/11
TI  - A Frame-Based Extended MIDI-Pitch Detection Algorithm Based on Variable Sampling Technology
BT  - Proceedings of the 2018 3rd International Conference on Communications, Information Management and Network Security (CIMNS 2018)
PB  - Atlantis Press
SP  - 29
EP  - 34
SN  - 2352-538X
UR  - https://doi.org/10.2991/cimns-18.2018.7
DO  - 10.2991/cimns-18.2018.7
ID  - Feng2018/11
ER  -