Chia-Min Lin tomonidan Musiac Musiqiy Tavsiyanoma Xizmati

Chia-Min Lin tomonidan yaratilgan Musiac Musiqiy Tavsiyanoma Xizmati — Interfeys, Interaktiv va Foydalanuvchi Tajribasi Dizayni tanlov toifasida nufuzli 2020 A' Design Award Kumush Mukofoti mukofotining yuqori baholangan g'olibidir.

KumushInterfeys· 2020

Musiac Musiqiy Tavsiyanoma Xizmati

muallif: Chia-Min Lin

Mijoz: LinStudio

Interfeys toifasida A' Design Award Kumush Mukofoti g'olibi

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Tasdiqlangan mukofot g'olibi

#91014 uchun mukofot holatini tasdiqlash

A' Design Award saytida ko'rish Press-reliz Mukofot nishoni

Ranglar

Dizayn

Musiac Musiqiy Tavsiyanoma Xizmati haqida

Musiac musiqiy tavsiya vositasi bo'lib, uning foydalanuvchilari uchun aniq variantlarni topish uchun faol ishtirok etishdan foydalaning. Bu algoritm avtokratiyasini shubha ostiga qo'yish uchun alternativ interfeyslarni taklif qilishni maqsad qiladi. Axborotni filtrlash muqarrar izlash usuliga aylandi. Shu bilan birga, u echo-kamera effektlarini yaratadi va foydalanuvchilarni o'zlarining qulaylik zonalarida ularning xohishlariga qat'iy rioya qilishlari bilan cheklaydi. Foydalanuvchilar passiv bo'lib qoladilar va mashinaning imkoniyatlari haqida savol berishni to'xtatadilar. Variantlarni ko'rib chiqishga vaqt sarflash katta bio-tannarxni oshirishi mumkin, ammo bu juda muhim tajriba yaratishga qodir kuchdir.

Tan olinish

A' Design Award Kumush Mukofoti haqida

Musiac Musiqiy Tavsiyanoma Xizmati A' Design Award Kumush Mukofotining g‘olibi bo‘lib, bu go‘zal, ulug‘vor va ta’sirchan eng yuqori darajadagi dizaynlarga beriladigan favqulodda nufuzli e’tirofdir. Kumush g‘oliblari o‘z dizaynerlarining ajoyib mahorati, iste’dodi va o‘tkirligini ko‘rsatuvchi juda yorqin va o‘ta ijodiy asarlardir. Musiac Musiqiy Tavsiyanoma Xizmati ajoyib, namunaviy, diqqatga sazovor darajada kasbiy va chuqur innovatsion asar bo‘lishi kutiladi. A' Design Award Kumush Mukofotini qo‘lga kiritgan ushbu dizayn san’at, fan, dizayn va texnologiya chegaralarini kengaytiruvchi juda e’tiborga loyiq, tahsinga sazovor ixtirodir. Musiac Musiqiy Tavsiyanoma Xizmati ko‘pchilik havas qiladigan, istaklarni uyg‘otadigan, ijobiy tuyg‘ular olib keladigan hamda hayrat va ajablanish uyg‘otadigan ijoddir.

Dizayn ortida

Press-kit

Dizayner tomonidan taqdim etilgan kreditlar, jamoa a'zolari va texnik tafsilotlar.

Noyob xususiyatlar: 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.
O'lchamlar va qadoqlash: 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.
Teglar: Algorithm autocracy, Ethical interface, Information architecture, Data visualization, User empowerment, Collaborative filtering
Ishlab chiqarish texnologiyasi: 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.
Dizayn muammosi: 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.
Tadqiqot: 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.
Ilhom: 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.
Loyiha muddati: Musiac was a one year project done in 2018, Detroit.
Ish jarayoni: 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.
Rasm mualliflari: All materials required in this project doesn't need attributions. Licenses are attached in the documentation appendix.