A2D: Anywhere Anytime Drumming

Harel Yadid; Almog Algranti; Mark Levin; Ayal Taitler

doi:10.1109/TENSYMP55890.2023.10223631

A2D: Anywhere Anytime Drumming

Harel Yadid
, Almog Algranti
, Mark Levin
, Ayal Taitler

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The drum kit, which has only been around for around 100 years, is a popular instrument in many music genres such as pop, rock, and jazz. However, the road to owning a kit is expensive, both financially and space-wise. Also, drums are more difficult to move around compared to other instruments, as they do not fit into a single bag. We propose a no-drums approach that uses only two sticks and a smartphone or a webcam to provide an air-drumming experience. The detection algorithm combines deep learning tools with tracking methods for an enhanced user experience. Based on both quantitative and qualitative testing with humans-in-the-loop, we show that our system has zero misses for beginner level play and negligible misses for advanced level play. Additionally, our limited human trials suggest potential directions for future research.

Original language	English
Title of host publication	2023 IEEE Region 10 Symposium, TENSYMP 2023
Publisher	Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781665482585
DOIs	https://doi.org/10.1109/TENSYMP55890.2023.10223631
State	Published - 1 Jan 2023
Externally published	Yes
Event	2023 IEEE Region 10 Symposium, TENSYMP 2023 - Canberra, Australia Duration: 6 Sep 2023 → 8 Sep 2023

Publication series

Name	2023 IEEE Region 10 Symposium, TENSYMP 2023

Conference

Conference	2023 IEEE Region 10 Symposium, TENSYMP 2023
Country/Territory	Australia
City	Canberra
Period	6/09/23 → 8/09/23

Keywords

Deep Learning
Musical instrumentation
Optimal Estimation

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Computer Vision and Pattern Recognition
Safety, Risk, Reliability and Quality
Instrumentation

Access to Document

10.1109/TENSYMP55890.2023.10223631

Cite this

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title = "A2D: Anywhere Anytime Drumming",

abstract = "The drum kit, which has only been around for around 100 years, is a popular instrument in many music genres such as pop, rock, and jazz. However, the road to owning a kit is expensive, both financially and space-wise. Also, drums are more difficult to move around compared to other instruments, as they do not fit into a single bag. We propose a no-drums approach that uses only two sticks and a smartphone or a webcam to provide an air-drumming experience. The detection algorithm combines deep learning tools with tracking methods for an enhanced user experience. Based on both quantitative and qualitative testing with humans-in-the-loop, we show that our system has zero misses for beginner level play and negligible misses for advanced level play. Additionally, our limited human trials suggest potential directions for future research.",

keywords = "Deep Learning, Musical instrumentation, Optimal Estimation",

author = "Harel Yadid and Almog Algranti and Mark Levin and Ayal Taitler",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Region 10 Symposium, TENSYMP 2023 ; Conference date: 06-09-2023 Through 08-09-2023",

year = "2023",

month = jan,

day = "1",

doi = "10.1109/TENSYMP55890.2023.10223631",

language = "English",

series = "2023 IEEE Region 10 Symposium, TENSYMP 2023",

publisher = "Institute of Electrical and Electronics Engineers",

booktitle = "2023 IEEE Region 10 Symposium, TENSYMP 2023",

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}

TY - GEN

T1 - A2D

T2 - 2023 IEEE Region 10 Symposium, TENSYMP 2023

AU - Yadid, Harel

AU - Algranti, Almog

AU - Levin, Mark

AU - Taitler, Ayal

PY - 2023/1/1

Y1 - 2023/1/1

N2 - The drum kit, which has only been around for around 100 years, is a popular instrument in many music genres such as pop, rock, and jazz. However, the road to owning a kit is expensive, both financially and space-wise. Also, drums are more difficult to move around compared to other instruments, as they do not fit into a single bag. We propose a no-drums approach that uses only two sticks and a smartphone or a webcam to provide an air-drumming experience. The detection algorithm combines deep learning tools with tracking methods for an enhanced user experience. Based on both quantitative and qualitative testing with humans-in-the-loop, we show that our system has zero misses for beginner level play and negligible misses for advanced level play. Additionally, our limited human trials suggest potential directions for future research.

AB - The drum kit, which has only been around for around 100 years, is a popular instrument in many music genres such as pop, rock, and jazz. However, the road to owning a kit is expensive, both financially and space-wise. Also, drums are more difficult to move around compared to other instruments, as they do not fit into a single bag. We propose a no-drums approach that uses only two sticks and a smartphone or a webcam to provide an air-drumming experience. The detection algorithm combines deep learning tools with tracking methods for an enhanced user experience. Based on both quantitative and qualitative testing with humans-in-the-loop, we show that our system has zero misses for beginner level play and negligible misses for advanced level play. Additionally, our limited human trials suggest potential directions for future research.

KW - Deep Learning

KW - Musical instrumentation

KW - Optimal Estimation

UR - https://www.scopus.com/pages/publications/85173497729

U2 - 10.1109/TENSYMP55890.2023.10223631

DO - 10.1109/TENSYMP55890.2023.10223631

M3 - Conference contribution

AN - SCOPUS:85173497729

T3 - 2023 IEEE Region 10 Symposium, TENSYMP 2023

BT - 2023 IEEE Region 10 Symposium, TENSYMP 2023

PB - Institute of Electrical and Electronics Engineers

Y2 - 6 September 2023 through 8 September 2023

ER -

A2D: Anywhere Anytime Drumming

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this