Musiac Suab Paj Nruag Lus Pom Zoo Muab Kev Pabcuam los ntawm Chia-Min Lin

Qhov qauv tsim Musiac Suab Paj Nruag Lus Pom Zoo Muab Kev Pabcuam los ntawm Chia-Min Lin yog tus yeej muaj nqis heev ntawm qhov khoom plig 2020 A' Design Award Nyiaj hauv Pawg Sib Tw Tsim Kev Sib Txuas, Kev Sib Cuam Tshuam thiab Kev Siv Neeg.

NyiajKev Sib Txuas· 2020

Musiac Suab Paj Nruag Lus Pom Zoo Muab Kev Pabcuam

los ntawm Chia-Min Lin

Tus Neeg Siv: LinStudio

Tus Yeej A' Design Award Nyiaj hauv Pawg Kev Sib Txuas

55,925

Tus Yeej Khoom Plig Tau Txheeb Xyuas

Txheeb Xyuas Qhov Xwm Txheej Khoom Plig rau #91014

Saib ntawm A' Design Award Tsab Xov Xwm Daim Phiaj Khoom Plig

Xim

Qhov Tsim

Txog Musiac Suab Paj Nruag Lus Pom Zoo Muab Kev Pabcuam

Musiac yog lub suab paj nruas pom zoo lub cav, siv cov koom nrog sawv daws kom paub cov lus qhia meej rau nws cov neeg siv. Nws lub hom phiaj yog thov qhia lwm qhov cuam tshuam los cuam tshuam rau lub algorithm autocracy. Cov ntaub ntawv lim tau dhau los ua ib qho kev tsis pom nruam nrhiav. Txawm li cas los xij, nws tsim cov kev cuam tshuam echo chamber thiab txwv cov neeg siv hauv lawv qhov chaw xis los ntawm strickly ua raws lawv nyiam. Cov neeg siv dhau los ua dhau thiab nres nug cov kev xaiv uas lub tshuab muab tau. Kev siv sijhawm los tshuaj xyuas cov kev xaiv yuav nce nqi ntawm bio loj, tab sis nws yog kev siv zog ua kom muaj kev paub zoo.

Qhov Lees Paub

Txog A' Design Award Nyiaj

Musiac Suab Paj Nruag Lus Pom Zoo Muab Kev Pabcuam yog tus yeej ntawm A' Design Award Nyiaj, ib qho kev lees paub muaj meej mom heev tshaj li qub uas muab rau cov qauv tsim qib siab, zoo nkauj thiab ua rau neeg xav tsis thoob. Cov neeg yeej Nyiaj yog cov haujlwm ci ntsa iab heev thiab tsim tshiab heev uas qhia txog kev paub, kev txawj ntse thiab kev ntse ntawm cov kws tsim qauv. Musiac Suab Paj Nruag Lus Pom Zoo Muab Kev Pabcuam xav tias yuav yog ib qho haujlwm zoo kawg nkaus uas tsim rau qhia, tshaj lij heev thiab tsim tshiab tob. Cov qauv tsim yeej A' Design Award Nyiaj no yog ib qho khoom tsim uas pom tseeb heev thiab neeg qhuas uas pab tau thiab nthuav dav ciam teb ntawm kev kos duab, kev tshawb fawb, kev tsim qauv thiab thev naus laus zis. Musiac Suab Paj Nruag Lus Pom Zoo Muab Kev Pabcuam yog ib qho khoom tsim uas neeg coob xav tau, uas ua rau xav, coj kev xav zoo thiab ua rau xav tsis thoob thiab xav paub.

Tom Qab Qhov Tsim

Pob Xov Xwm

Cov credit, cov neeg pab thiab cov ntsiab lus kev txawj ntse muab los ntawm tus tsim.

Yam Tshwj Xeeb: Musiac is a music recommendation service aims to provide better selection mechanism. It uses a contour map to represent all musical genres in a single interface, showing the relationship across songs and genres in a 2D space. It maps out a taste bubble from the user's playlists, separating the user's prior musical taste field from the unexplored musical territory. The user can change the outline of the bubble by dragging it and expanding the scope of the recommendation algorithm.
Qhov Loj & Ntim: Musiac is a desktop application. It requires a user to import his/her playlists of third-party apps to build the "Taste Bubble" at the beginning. The bubble sits on an algorithmically-generated genres map, with a horizontal (electric, acoustic) and a vertical (atmospheric, bouncier) indication. The bubble separates the familiar and unexplored territory for a user so he/she could expand the recommendation (temporarily), without changing their behavior.
Cov Ntsiab Lus: Algorithm autocracy, Ethical interface, Information architecture, Data visualization, User empowerment, Collaborative filtering
Thev Naus Laus Zis Tsim Khoom: Musiac learns from "Every Noise at Once", has a virtual database, a theoretical possible algorithmically-generated map, and an ethical interface to reduce the bio-cost of finding liked songs from enormous options. It starts with a study of recommendation engines and filters, interviews, and a pre-testing, then ideates with "what if" questions along the generative design process, run through 2 round of user-testing to validate initial concepts and iterates. The project took a year to finalize.
Kev Sib Tw Tsim Qauv: The most difficult part of this project is to find an industry professional to talk to me. Online streaming service is a very competitive field. Hence, business and advertising dominate the final result of music recommendations, which creates intransparent and unethical algorithms. Academics and scholars provide enthusiastic feedback, but one of the business executives cancel his help after he saw my questions list.
Another major research constrains is the fuzzy relationships of million users' playlists. Single users' taste bubble might not accommodate with the overarching dimensions, even though the machine could easily map his or her playlists into an individual lump. After I consulted with the famous founder of EveryNoise, he gives me great advice that I should have customized dimensions for different users to solve this issue. The system could map out the contour map from each individual users perspective, based on what's the location of the taste bubble, then decide how to show the rest of the genres. Despite the computation power is not efficient enough for this project, but this solution is definitely feasible at the nearby future.
Kev Tshawb Fawb: Musiac ran with a waterfall and agile hybrid methodology: research, framing, prototype, test, and reflecting. Feedback was collected along the way and therefore, multiple iterations. I did solid case studies, interviewed active and passive music online streaming users, and consulted with programmers to finalize the proper frame of this project. Multiple user testings with a clickable prototype were performed in-person, as well as online.
Kev Txhawb Siab: Musiac started with a simple notion. Interface is the tangent point between our perception and reality. I believe interface reflects a subtle world of why we make choices. I ran into a website called Every Noise at Once and found it's a perfect database to test my theory. Interface has a higher-level goal of helping us to process information better. I want to design something that goes beyond data visualization and empower users to be more proactive upon the world they're seeing.
Lub Sij Hawm Ua Hauj Lwm: Musiac was a one year project done in 2018, Detroit.
Txheej Txheem Ua Hauj Lwm: Musiac is a desktop application with an unusual interface, allows users to control the scope of recommendations and to manipulate the filtered results. It uses a bubble to separate the unexplored genres from the familiar genres. A user could easily change the shape of the bubble to expand the recommendation source. It also provides multiple filters, such as themes with different adjectives; numbers of views, finding songs with specific traits, and a guiding system to go beyond the comfort zone.
Kev Qhuas Duab: All materials required in this project doesn't need attributions. Licenses are attached in the documentation appendix.