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Chenyuan Cui

Research journal • 1. Color & Symbol

Research journal • 1. Color & Symbol • [1.1]John Gage, Color and Meaning: Art, Science, and

Symbolism, • [1.2]Charles J. Golden, The Measurement of Creativity by the Stroop Color and Word

Test, • [1.3]Erella Hovers, Shimon Ilani, Ofer Bar, An Early Case of Color Symbolism: Ochre Use by

Modern Humans in Qafzeh Cave, =21101172240237 • [1.4], • [1.5]Music Visualization: Beautiful Tools to ‘See’

Sound, (This site has a lot of sample) • [1.6]Visual Headphones,

Research journal • 2. Music & Lyrics Section

Research journal • 2. Music & Lyrics Section •

[2.1] Nick Zangwill, Music, Metaphor, and Emotion,

[2.2] Eric Nichols, Dan Morris, Sumit Basu and Christopher Raphael, Relationships between Lyrics and Melody in Popular Music,

[2.3] Lyrics Plugin,

[2.4] API ,

[2.5] Patricia M. Greenfield, etc, What is Rock Music Doing to the Minds of our Youth? A First Experimental Look at the Effects of Rock Music Lyrics and Music Videos,

[2.6] Cyril Laurier, Multimodal Music Mood Classification using Audio and Lyrics,

[2.7] Beth Logan, Andrew Kositsky, Pedro Moreno, Semantic Analysis of Song Lyrics,

Research journal • 3. Interaction Section

Research journal • Question 1 coordination: • How do you think of the connection between music and photos? • Question 2 interestingness: • How do you think of the presentation style? • Question 3 colorfulness: • How well do you think the visual contents enrich the audio?

Research journal • 3. Interaction Section •

[3.1] Elias Pampalk, Islands of Music, Analysis, Organization, and Visualization of Music Archives,

[3.2] Otmar Hilliges, P. Holzer, Rene Klüber, and Andreas Butz, Audio Radar: A metaphorical visualization for the navigation of large music collections,

[3.3] Chin-Han Chen, Ming-Fang Weng, Shyh-Kang Jeng, and Yung-Yu Chuang, Emotion-Based Music Visualization Using Photos,

[3.4] Honglak Lee, Yan Largman, Peter Pham, Andrew Y. Ng, Unsupervised feature learning for audio classification, using convolutional deep belief networks,

[3.5] Xian-Sheng HUA, Lie LU, Hong-Jiang ZHANG, Automatic Music Video Generation Based on Temporal Pattern Analysis,

[3.6] Music Genome Project,

[3.7] Spotify,

[3.8] Midomi,

[3.9] Songsmith, (Songsmith generates musical accompaniment to match a singer’s voice.)

[3.10] process software, Music Visualizer,

Research journal • Should: • More focus on the project and data visualization

Outline • Introduction • Basic Definitions • Music visualization • Real-time music visualization • Music Lyrics

• Problem statement • Scientist keep find the strange feature of music to visualize, arts keep using the random pattern to

visualize. Sometimes no ‘meaningful’. • Thesis Statement • Lyrics-based visualization can improve listeners' emotion in music. (Project introduction - overview)

• History of Music Visualization • Early age – visualized by person in advance • Later – try to auto-generated, sometimes add personal element • Now – more music features are detected. • Current Development Trends • By Music • Music genome project (Pandora) • Query by humming (Midomi) • Simple visualized software (Media player/ iPhone App)

• By People • More different languages songs are produced

Outline • Project Description • Design goals • Non-English speakers can better understand or experience the English songs.

• Solutions to immediate problem • song styles • lyrics types • Methodology • Methods • Lyrics analysis • why only English song • relationship between lyrics and melody

• Melody and other features analysis • Current APIs • • OpenAL

• Additional tools

• Design process • Idea • Design sketches • Prototyping • Development • Testing • Revision

Outline • Reception of My Project • Feedback • Observations • Others

• Conclusion • better understand music and so. • Further Works • Other type music • Other language lyrics

Task list & schedule • Now: • This project is a cross-subject project related to

Psychology, Computer Vision, Music, and Graphics.

• What I should do: • Refine the topic, focus on data visualization first!

Task list & schedule • Almost done in studio I: • Strengthen the knowledge of psychology; continue researching

on music, metaphor, emotion and the relationships between lyrics and melody. • Initially list what pattern and words will influence people’s emotion. • Then try to research more articles about the relationship among music, language and psychology and how they influence each other. • Start to make the interactive prototype. (The interface is more like an application) if the final project is an installation, I will consider how to build it, how to test it, and how many projectors will be used.

Task list & schedule • To be done: • Keep refining "Studio I". • Coding, then test the pre-built and real-time visualization

by using API. • Testing, refine the algorithm based the lyrics context. • Once the above is finished, start to collect the data from testing people. What is the feeling of same people when see the visualized music or not. • At the end of the project, process and analysis those data, to finish the paper.

Task list & schedule


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