Score-Tool: target audibility testing in orchestration
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Helsinki
Sibelius Academy of the University of the Arts Helsinki
2023
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| Schriftenreihe: | EST
n° 72 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Taiteilijakoulutuksen tohtorintutkintoon liittyvä kirjallinen työ |
| Beschreibung: | 173 Seiten Illustrationen, Diagramme, Notenbeispiele |
| ISBN: | 9789523293090 |
Internformat
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Datensatz im Suchindex
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TABLE OF CONTENTS INTRODUCTION . 1 Motivation. 1 The purpose of the project. 3 Benefits of computational audibility testing. 4 Trivial and non-trivial audibility issues. 5 How CAN THE AUDIBILITY OF A TARGET BE TESTED?. 5 Objectives. 7 Personal objectives. 7 Other objectives.7 The body of the Score-Tool project. 8 PARTI BACKGROUND. 9 1 Orchestration. 9 2 Methods. 9 3 Orchestration handbook
overview.10 3.1 The books selected for overview.10 3.2 How AUDIBILITY IS ADDRESSED IN FOUR ORCHESTRATION HANDBOOKS. 10 3.3 Overview of The Berlioz-Strauss and Rimsky-Korsakov orchestration HANDBOOKS. 11 3.4 Overview of Piston’s and Adler’s orchestration handbooks. 15 3.5 Conclusion of orchestration handbook overview. 20 4 Aspects of our hearing system related to the project. 21 5 Concepts used in the report. 27 5.1 Pitch and frequency. 27 5.2 Harmonics/overtones. 27 5.3 Loudness. 27 5.4 Critical band. 28 5.5 Auditory masking. 29 5.6 Spectral masking. 29 5.7 Sine wave masking sine
wave. 30 5.8 Masking of complex tones. 31 5.9 Terhardt’s virtual pitch. 32 5.10 Spectral dominant region. 33 5.11 Informational masking. 34 6 Orchestration in the digital era: can techniques used by recording ENGINEERS BE APPLIED TO ACOUSTIC ORCHESTRATION?. 34
6.1 The recording engineer as orchestrator. 34 6.2 My artistic interest in the recording engineer’s work.35 6.3 What an orchestral composer can learn from a recording engineer .37 6.4 Instrument placement in the hall and audibility. 39 6.5 Conclusion of the digital orchestration chapter. 43 7 Audibility and blending of musical instruments. 43 Previous research on blending musical sounds. 43 7.1 7.2 Blending and homogeneity of the timbre. 44 7.3 Blending and instrument formant areas. 44 7.4 The Horn as a good blender.45 7.5 The spectral centroid and blending. 45 7.6 The benefit of low dynamics to blending. 46 7.7 Musical dissonance and blending.47 7.8 Musical register and blending. 48 7.9 Conclusion about previous research on blending. 48 8 Previous research on masking in the context of musical sounds. 49 9 Previous research on computer-aided
orchestration. 51 10 The effect of the concert hall on the audibility of an instrument . 54 10.1 Hall reverberation. 54 10.2 Orchestra seating.55 10.3 Critical distance.56 10.4 The listener’s preference. 56 11 Previous research on auditory perception related to the project . 57 11.1 MIR AND TIMBRE FEATURES. 57 11.2 Musical cocktail party. 58 11.3 How many concurrent timbres can we hear?. 59 11.4 Musical stream. 60 12 Timbre and stream creation. 61 12.1 Unconscious habits that make instruments audible. 62 12.2 Conclusion of the perception chapter. 64 PART II THE SCORE-TOOL APP. 65 1 Basic structure of the Score-Tool
App.65 2 The Score-Tool instrument database. 67 3 Implementing algorithms. 68 4 Mathematics used in the Score-Tool project. 68
4.1 Digital representation of sound waves. 68 4.2 The Fourier transform. 68 4.3 Bark. 69 4.4 Mel scale.70 4.5 Cepstrum.70 4.6 MFCC. 71 4.7 The spectral centroid. 71 4.8 Masking spreading function. 72 4.9 Coefficient of variation. 72 4.10 Terhardt’s spectral dominant region formula. 73 5 Interpreting dynamic markings in orchestral score. 74 5.1 Orchestral instrument dynamics in Score-Tool. 74 5.2 The dynamic palette. 74 5.3 Marking dynamics for concurrent timbres. 76 5.4 How dynamics affect
timbre. 79 5.5 Measuring an instrument’s dynamics. 80 5.6 Directionality of the instrument sound. 81 5.7 From dynamics to decibels.83 6 My own measurements in orchestra rehearsals. 86 7 Preparing analytical data for the Score-Tool App. 88 8 Analysis models adapted and developed for Score-Tool. 93 8.1 MPEG LOSSY CODING. 93 8.2 Why I want to use the MPEG psychoacoustic model. 94 8.3 How the MPEG psychoacoustic model works. 94 8.4 The psychoacoustic model in the Score-Tool App. 94 8.5 Target audibility prediction in Score-Tool App.96 8.6 Homogeneity of orchestration. 99 8.7 Coefficient of variation. 100 8.8 Comparison of MFCC vectors. 100 8.9 Conclusion about timbre homogeneity. 102 9 Data
Visualization. 102 9.1 Fuzzy data. 103 9.2 Statistical data visualization. 103 9.3 Audibility visualization model. 104 9.4 Masking graph visualization choices explained. 105 9.5 Staff graph - redundant information. 107
10 Features of the Score-Tool App. 108 10.1 Tutorial. 110 10.2 Chord. 112 10.3 Compare.120 10.4 Score. 122 PART III TESTING. 129 1 Why and what is tested?. . 129 2 Artistic testing: an opera. 129 3 2.1 Programming and composition work.130 2.2 The computer and creativity. 132 2.3 The opera. 133 2.4 Score-Tool and the opera. 133 2.5 How the Score-Tool App affects my artistic decisions. 137 2.6 Score-Tool in my
composition workflow. 139 2.7 Experiences in opera rehearsals and performances. 139 Peer testing. 143 3.1 SONORITY - HORN CONCERTO, NOVEMBER 2, 2021 .143 3.2 Field test 2, September 28,2021. 148 3.3 Field test 1, January 30,2020. 151 EPILOGUE AND FUTURE RESEARCH.160 3.4 Future research. 162 GLOSSARY OF TERMS. 163 REFERENCES 168 |
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| spelling | Pulkkis, Uljas 1975- Verfasser (DE-588)133453995 aut Score-Tool target audibility testing in orchestration doctoral project by Uljas Pulkkis Helsinki Sibelius Academy of the University of the Arts Helsinki 2023 173 Seiten Illustrationen, Diagramme, Notenbeispiele txt rdacontent n rdamedia nc rdacarrier EST n° 72 Taiteilijakoulutuksen tohtorintutkintoon liittyvä kirjallinen työ Doctoral project, written report University of the Arts Helsinki Programm (DE-588)4047394-6 gnd rswk-swf Hörprüfung (DE-588)4123388-8 gnd rswk-swf Orchestration (DE-588)4172713-7 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Orchestration (DE-588)4172713-7 s Programm (DE-588)4047394-6 s Hörprüfung (DE-588)4123388-8 s DE-604 Erscheint auch als Online-Ausgabe 978-952-329-301-4 EST n° 72 (DE-604)BV017725787 72 Digitalisierung BSB München - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=035146725&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Pulkkis, Uljas 1975- Score-Tool target audibility testing in orchestration EST Programm (DE-588)4047394-6 gnd Hörprüfung (DE-588)4123388-8 gnd Orchestration (DE-588)4172713-7 gnd |
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| title | Score-Tool target audibility testing in orchestration |
| title_auth | Score-Tool target audibility testing in orchestration |
| title_exact_search | Score-Tool target audibility testing in orchestration |
| title_full | Score-Tool target audibility testing in orchestration doctoral project by Uljas Pulkkis |
| title_fullStr | Score-Tool target audibility testing in orchestration doctoral project by Uljas Pulkkis |
| title_full_unstemmed | Score-Tool target audibility testing in orchestration doctoral project by Uljas Pulkkis |
| title_short | Score-Tool |
| title_sort | score tool target audibility testing in orchestration |
| title_sub | target audibility testing in orchestration |
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| topic_facet | Programm Hörprüfung Orchestration Hochschulschrift |
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