Musiac Tseirbhís Molta Ceoil le Chia-Min Lin

Is buaiteoir an-mheasúil den ghradam fíor-ardghradamach 2020 Duais Airgid A' Design Award sa Chatagóir Comórtais Dearadh Comhéadain é an dearadh Musiac Tseirbhís Molta Ceoil le Chia-Min Lin.

AirgeadComhéadan· 2020

Musiac Tseirbhís Molta Ceoil

le Chia-Min Lin

Cliant: LinStudio

Buaiteoir an ghradaim Duais Airgid A' Design Award sa Chatagóir Comhéadan

57,305

Buaiteoir Gradaim Fíoraithe

Fíoraigh Stádas Gradaim do #91014

Féach ag A' Design Award Preasráiteas Suaitheantas Gradaim

Dathanna

An Dearadh

Maidir le Musiac Tseirbhís Molta Ceoil

Is inneall molta ceoil é Musiac, bain úsáid as rannpháirtíocht réamhghníomhach chun roghanna beachta a fháil dá úsáideoirí. Tá sé mar aidhm aige comhéadain mhalartacha a mholadh chun dúshlán a thabhairt d’uathachas an algartam. Is cur chuige dosheachanta cuardaigh é scagadh faisnéise. Mar sin féin, cruthaíonn sé éifeachtaí seomra macalla agus cuireann sé srian ar úsáideoirí ina gcrios chompord trí leanúint dá roghanna. Éiríonn úsáideoirí éighníomhach agus stopann siad ag ceistiú na roghanna a sholáthraíonn an meaisín. D’fhéadfadh bith-chostas ollmhór a bheith ag caitheamh ama chun roghanna a athbhreithniú, ach is í an iarracht a chruthaíonn eispéireas bríoch.

An Aitheantas

Maidir leis an Duais Airgid A' Design Award

Bhuaigh an dearadh Musiac Tseirbhís Molta Ceoil Duais Airgid A' Design Award, aitheantas an-ghradamach a bhronntar ar dhearaí ardchaighdeáin, álainn agus drámatach. Is saothair thar a bheith drithleacha agus an-chruthaitheach iad buaiteoirí Airgid a léiríonn saineolas, tallann agus géarchúis shármhaith a ndearthóirí. Táthar ag súil go mbeidh an dearadh Musiac Tseirbhís Molta Ceoil ina shaothar iontach, ina léiriú sampla, thar a bheith gairmiúil agus go domhain nuálach. Is aireagán an-suntasach, ionadmhuirthe é an dearadh seo a bhuaigh Duais Airgid A' Design Award a dhéanann leas do theorainneacha na healaíne, na heolaíochta, an deartha agus na teicneolaíochta agus a chuireann chun cinn iad. Is cruthú é an dearadh Musiac Tseirbhís Molta Ceoil a bhfuil formad mór leis, a mhúsclaíonn mianta, a thugann mothúcháin dhearfacha agus a adhnann iontas agus ionadh.

Taobh Thiar den Dearadh

Pacáiste Preasa

Creidiúintí, baill foirne agus sonraí teicniúla curtha ar fáil ag an dearthóir.

Airíonna Uathúla: 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.
Toisí & Pacáistiú: 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.
Clibeanna: Algorithm autocracy, Ethical interface, Information architecture, Data visualization, User empowerment, Collaborative filtering
Teicneolaíocht Táirgthe: 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.
Dúshlán Deartha: 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.
Taighde: 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.
Inspioráid: 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.
Fad an Tionscadail: Musiac was a one year project done in 2018, Detroit.
Sreabhadh Oibríochta: 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.
Creidiúintí Íomhá: All materials required in this project doesn't need attributions. Licenses are attached in the documentation appendix.