NDLI: ChordRipple: Adaptively Recommending and Propagating Chord Changes for Songwriters

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ChordRipple: Adaptively Recommending and Propagating Chord Changes for Songwriters

Content Provider	ACM Digital Library
Author	Huang, Cheng-Zhi Anna
Abstract	Songwriting is the interplay of a composer's creative intent and an idiom's language. This language both facilitates and poses stylistic constraints on a composer's expressivity. Novice composers often find it difficult to go beyond common chord progressions, to find the chords that realize their intentions. To make it easier for composers to experiment with radical chord choices and to prototype "what-if" ideas, we are building a creativity support tool, ChordRipple, which (1) makes chord recommendations that aim to be both diverse and appropriate to the current context, (2) infers a composer's intention to help her more quickly prototype ideas. Composers can use it to help select the next chord, to replace sequences of chords in an internally consist manner, or to edit one part of a sequence and see the whole sequence change in that direction. To make such recommendations, we adapt neural-network models such as Word2Vec to the music domain as Chord2Vec. This model learns chord embeddings from a corpus of chord sequences, placing chords nearby when they are used in similar contexts. The learned embeddings support creative substitutions between chords, and also exhibit topological properties that correspond to musical structure. For example, the major and minor chords are both arranged in the latent space in shapes corresponding to the circle-of-fifths. To support the dynamic nature of the creative process, we propose to infer a composer's intentions for adaptive recommendation. As a composer makes chord changes, she is moving in the embedding space. We can infer a composer's intention from the gradient of her edits' trace and use this gradient to help her fine-tune her current changes or to project the sequence into the future to give recommendations on how the sequence could look like if more edits in that direction were performed.
Starting Page	138
Ending Page	141
Page Count	4
File Format	PDF
ISBN	9781450341400
DOI	10.1145/2876456.2876465
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-03-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Creativity support tools Intelligent user interfaces Harmony Music Neural language models Songwriting Recommender systems
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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