Score-Informed Analysis of Tuning, Intonation, Pitch Modulation, and Dynamics in Jazz Solos

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Standard

Score-Informed Analysis of Tuning, Intonation, Pitch Modulation, and Dynamics in Jazz Solos. / Abeber, Jakob; Frieler, Klaus; Cano, Estefania et al.

in: IEEE/ACM Transactions on Audio Speech and Language Processing, Jahrgang 25, Nr. 1, 01.2017, S. 168-177.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Harvard

APA

Vancouver

Bibtex

@article{886f19029d874e46808748de654fe43d,
title = "Score-Informed Analysis of Tuning, Intonation, Pitch Modulation, and Dynamics in Jazz Solos",
abstract = "Both the collection and analysis of large music repertoires constitute major challenges within musicological disciplines such as jazz research. Automatic methods of music analysis based on audio signal processing have the potential to assist researchers and to accelerate the transcription and analysis of music recordings significantly. In this paper, we propose a framework for analyzing improvised monophonic solos in multi-instrumental jazz recordings with special focus on reed and brass instruments. The analysis algorithms rely on prior score-information, which is taken from high quality manual solo transcriptions. Following an initial solo and accompaniment source separation, we propose algorithms for tone-wise extraction of fundamental frequency and intensity contours. Based on this fine-grained representation of recorded jazz solos, we perform several exploratory experiments motivated by questions relating to jazz research in order to analyze the use of expressive stylistic devices such as intonation, pitch modulation, and dynamics in jazz solos. The results show that a score-informed audio analysis of jazz recordings can provide valuable insights into the individual stylistic characteristics of jazz musicians.",
keywords = "Dynamics, fundamental frequency contours, Jazz research, music analysis, score-informed audio analysis, source separation, Music education",
author = "Jakob Abeber and Klaus Frieler and Estefania Cano and Martin Pfleiderer and Zaddach, {Wolf Georg}",
year = "2017",
month = jan,
doi = "10.1109/TASLP.2016.2627186",
language = "English",
volume = "25",
pages = "168--177",
journal = "IEEE/ACM Transactions on Audio Speech and Language Processing",
issn = "2329-9290",
publisher = "IEEE Advancing Technology for Humanity",
number = "1",

}

RIS

TY - JOUR

T1 - Score-Informed Analysis of Tuning, Intonation, Pitch Modulation, and Dynamics in Jazz Solos

AU - Abeber, Jakob

AU - Frieler, Klaus

AU - Cano, Estefania

AU - Pfleiderer, Martin

AU - Zaddach, Wolf Georg

PY - 2017/1

Y1 - 2017/1

N2 - Both the collection and analysis of large music repertoires constitute major challenges within musicological disciplines such as jazz research. Automatic methods of music analysis based on audio signal processing have the potential to assist researchers and to accelerate the transcription and analysis of music recordings significantly. In this paper, we propose a framework for analyzing improvised monophonic solos in multi-instrumental jazz recordings with special focus on reed and brass instruments. The analysis algorithms rely on prior score-information, which is taken from high quality manual solo transcriptions. Following an initial solo and accompaniment source separation, we propose algorithms for tone-wise extraction of fundamental frequency and intensity contours. Based on this fine-grained representation of recorded jazz solos, we perform several exploratory experiments motivated by questions relating to jazz research in order to analyze the use of expressive stylistic devices such as intonation, pitch modulation, and dynamics in jazz solos. The results show that a score-informed audio analysis of jazz recordings can provide valuable insights into the individual stylistic characteristics of jazz musicians.

AB - Both the collection and analysis of large music repertoires constitute major challenges within musicological disciplines such as jazz research. Automatic methods of music analysis based on audio signal processing have the potential to assist researchers and to accelerate the transcription and analysis of music recordings significantly. In this paper, we propose a framework for analyzing improvised monophonic solos in multi-instrumental jazz recordings with special focus on reed and brass instruments. The analysis algorithms rely on prior score-information, which is taken from high quality manual solo transcriptions. Following an initial solo and accompaniment source separation, we propose algorithms for tone-wise extraction of fundamental frequency and intensity contours. Based on this fine-grained representation of recorded jazz solos, we perform several exploratory experiments motivated by questions relating to jazz research in order to analyze the use of expressive stylistic devices such as intonation, pitch modulation, and dynamics in jazz solos. The results show that a score-informed audio analysis of jazz recordings can provide valuable insights into the individual stylistic characteristics of jazz musicians.

KW - Dynamics

KW - fundamental frequency contours

KW - Jazz research

KW - music analysis

KW - score-informed audio analysis

KW - source separation

KW - Music education

UR - http://www.scopus.com/inward/record.url?scp=85007490276&partnerID=8YFLogxK

U2 - 10.1109/TASLP.2016.2627186

DO - 10.1109/TASLP.2016.2627186

M3 - Journal articles

AN - SCOPUS:85007490276

VL - 25

SP - 168

EP - 177

JO - IEEE/ACM Transactions on Audio Speech and Language Processing

JF - IEEE/ACM Transactions on Audio Speech and Language Processing

SN - 2329-9290

IS - 1

ER -

DOI