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Musical punctuation on the microlevel

Automatic identification and performance of small melodic units

Bibliographic Data

ID5304809
AuthorsAnders Friberg (0000-0002-8164-2819, KTH Royal Institute of Technology), Roberto Bresin (0000-0002-3086-0322, KTH Royal Institute of Technology), Lars Frydén (KTH Royal Institute of Technology), Johan Sundberg (0000-0002-7234-7551, KTH Royal Institute of Technology)
Year1998
Volume27
Issue3
Pages271-292
Publication date1998-09-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of New Music Research (JOURNAL)
Journal identifiersISSN: 0929-8215 • E-ISSN: 1744-5027
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/09298219808570749
OpenAlexW2028551496
LanguageEN
Citations received12
References cited10

In this investigation we use the term musical punctuation for the marking of melodic structure by commas inserted at the boundaries that separate small structural units. Two models are presented that automatically try to locate the positions of such commas. They both use the score as the input and operate with a short context of maximally five notes. The first model is based on a set of subrules. One group of subrules mark possible comma positions, each provided with a weight value. Another group alters or removes these weight values according to different conditions. The second model is an artificial neural network using a similar input as that used by the rule system. The commas proposed by either model are realized in terms of micropauses and of small lengthenings of interonset durations. The models are evaluated by using a set of 52 musical excerpts, which were marked with punctuations according to the preference of an expert performer

Artificial neural network · Melody · Musical · Natural language processing · Punctuation · Speech recognition · Computer Science · Music and Audio Processing · Music Technology and Sound Studies · Neuroscience and Music Perception · Artificial Intelligence

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Unique citing works12
Citations per year0,43
Citation span1998 - 2025 (28)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 6
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