Chia-Min Lin diseinatzailearen Musiac Musika Gomendio Zerbitzua

Chia-Min Lin diseinatzailearen Musiac Musika Gomendio Zerbitzua lana 2020 Zilarrezko Saria A' Design Award sari ospetsuaren irabazle bikaina da Interfaze, Elkarrekintza eta Erabiltzaile Esperientzia Diseinua Lehiaketa Kategorian.

ZilarInterfazea· 2020

Musiac Musika Gomendio Zerbitzua

diseinatzailea: Chia-Min Lin

Bezeroa: LinStudio

Zilarrezko Saria A' Design Award Irabazlea Interfazea Kategorian

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Egiaztatutako Sari Irabazlea

#91014 Sariaren Egoera Egiaztatu

A' Design Award-en Ikusi Prentsa-oharra Sari-bereizgarria

Koloreak

Diseinua

Musiac Musika Gomendio Zerbitzua Diseinuari Buruz

Musiac gomendio musikalaren motorra da, parte-hartze proaktiboa erabili erabiltzaileen aukera zehatzak aurkitzeko. Interfaz alternatiboak proposatu nahi ditu algoritmoaren autokrazia desafiatzeko. Informazioa iragaztea bilaketa ezin hobea izan da. Hala ere, oihartzunaren ganbera-efektuak sortzen ditu eta erabiltzaileak beren erosotasun-eremuan mugatzen ditu lehentasunak zorrotz jarraituz. Erabiltzaileak pasiboak bihurtzen dira eta makinak eskaintzen dituen aukerak zalantzan jartzen dira. Aukerak berrikusteko denbora igarotzeak bio-kostu izugarria handitu dezake, baina esperientzia esanguratsua sortzen duen ahalegina da.

Aintzatespena

Zilarrezko Saria A' Design Award Sariari Buruz

Musiac Musika Gomendio Zerbitzua Zilarrezko Saria A' Design Award irabazlea da, goi-mailako, zoragarriak eta liluragarriak diren diseinuei ematen zaien ezohiko aitorpen prestijiotsua. Zilar-mailako irabazleak lan oso distiratsuak eta sormen biziko lanak dira, beren diseinatzaileen aditutasun, talentu eta zorroztasun nabarmenak erakusten dituztenak. Musiac Musika Gomendio Zerbitzua erakusleiho-lan zoragarria, nabarmenki profesionala eta sakonki berritzailea izatea espero da. Zilarrezko Saria A' Design Award irabazi duen diseinu hau asmakizun oso nabarmena eta miretsia da, onura ekartzen duena eta artearen, zientziaren, diseinuaren eta teknologiaren mugak zabaltzen dituena. Musiac Musika Gomendio Zerbitzua jende askok inbidia duen sorkuntza da, desirak pizten dituena, sentimendu positiboak ekartzen dituena eta harridura eta txunditzea pizten dituena.

Diseinuaren Atzean

Prentsa-kita

Diseinatzaileak emandako kredituak, taldekideak eta xehetasun teknikoak.

Propietate Bereziak: 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.
Neurriak eta Ontziratzea: 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.
Etiketak: Algorithm autocracy, Ethical interface, Information architecture, Data visualization, User empowerment, Collaborative filtering
Produkzio Teknologia: 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.
Diseinu Erronka: 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.
Ikerketa: 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.
Inspirazioa: 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.
Proiektuaren Iraupena: Musiac was a one year project done in 2018, Detroit.
Eragiketa Fluxua: 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.
Irudi Kredituak: All materials required in this project doesn't need attributions. Licenses are attached in the documentation appendix.