Music Recommendation Service for LinStudio
Musiac is a musical recommendation engine, utilize proactive participation to find precise options for its users. It aims to propose alternative interfaces to challenge the algorithm autocracy. Information filtering has become an inevitable searching approach. However, it creates echo chamber effects and constrains users in their comfort zone by strickly follow their preferences. Users become passive and stop questioning the options the machine provides. Spending time to review options may increase huge bio-cost, but it is the effort that creates a meaningful experience.
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Download Press Kit № 91014 Music Recommendation Service for LinStudio by Chia-Min Lin to access high-res images, essential texts, translations, and exclusive interviews—all in one.
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Exclusive Content: We offer an interview with Chia-Min Lin, approximately 1029 words in length, for journalists to use at no cost. Access and download now. Access Chia-Min Lin Interview Now.
Explore press materials for Musiac, available in languages such as English.
Bringing Musiac closer to you with translations in multiple languages: Хөгжмийн Зөвлөмж Үйлчилгээ MN, संगीत सिफारिश सेवा NE, Musikkanbefalingstjeneste NO, ସଂଗୀତ ସୁପାରିଶ ସେବା OR, Musiekaanbevelingsdiens AF, ਸੰਗੀਤ ਦੀ ਸਿਫਾਰਸ਼ ਸੇਵਾ PA, Shërbimi I Rekomandimit Të Muzikës SQ, سرویس توصیه موسیقی FA, የሙዚቃ የምክር አገልግሎት AM, Usługa Rekomendacji Muzycznych PL, خدمة التوصية بالموسيقى AR, د میوزیک سپارښتنې خدمت PS, Երաժշտության Առաջարկությունների Ծառայությունը HY, O Serviço De Recomendação De Música PT, Musiqi Tövsiyə Xidməti AZ, Serviciul De Recomandare Muzicală RO, Musika Gomendio Zerbitzua EU, Сервис Музыкальных Рекомендаций RU, Паслуга Рэкамендацыі Музыкі BE, موسيقي جي سفارش سروس SD, সংগীত প্রস্তাবনা পরিষেবা BN, Musika Fautuaga Auaunaga SM, Glazbena Preporuka Usluga BS, Музичка Препорука Услуга SR, Услугата За Препоръчване На Музика BG, Seirbheis Moladh Ciùil GD, ဂီတထောက်ခံချက်ဝန်ဆောင်မှု MY, Mumhanzi Kukurudzira Sevhisi SN, El Servei De Recomanacions Musicals CA, සංගීත නිර්දේශ සේවාව SI, Ntchito Yovomerezera Nyimbo NY, Služba Hudobných Odporúčaní SK, 音乐推荐服务 ZH, Glasbena Priporočila Storitev SL, U Serviziu Di Raccomandazione Di Musica CO, Adeegga Talo Bixinta Muusikada SO, Glazbena Preporuka Usluga HR, Tšebeletso Ea Litlhahiso Tsa Mmino ST, Hudební Doporučení CS, El Servicio De Recomendación Musical ES, Musikanbefalingstjeneste DA, Jasa Rekomendasi Musik SU, Muziekaanbevelingsservice NL, Huduma Ya Kupendekeza Muziki SW, Muzika Rekomendoservo EO, Musikrekommendationstjänst SV, Muusikasoovitusteenus ET, இசை பரிந்துரை சேவை TA, Musiikkisuosituspalvelu FI, సంగీత సిఫార్సు సేవ TE, Le Service De Recommandation Musicale FR, Хадамоти Тавсиядиҳии Мусиқӣ TG, O Servizo De Recomendacións Musicais GL, บริการแนะนำเพลง TH, მუსიკალური სარეკომენდაციო მომსახურება KA, Aýdym-Saz Maslahat Beriş Hyzmaty TK, Musikempfehlungsdienst DE, Ang Serbisyo Sa Rekomendasyon Ng Musika TL, Η Υπηρεσία Σύστασης Μουσικής EL, Müzik Öneri Hizmeti TR, સંગીત ભલામણ સેવા GU, Музыка Тәкъдим Итү Хезмәте TT, Sèvis Rekòmandasyon Mizik HT, مۇزىكا تەۋسىيە مۇلازىمىتى UG, Sabis Na Bayar Da Shawarar Kiɗa HA, Послуга Музичних Рекомендацій UK, Music Recommendation Service EN, שירות המלצות מוזיקה HE, موسیقی کی سفارش کی خدمت UR, संगीत सिफारिश सेवा HI, Musiqiy Tavsiyanoma Xizmati UZ, A Zenei Ajánlás Szolgáltatás HU, Dịch Vụ Giới Thiệu Âm Nhạc VI, Layanan Rekomendasi Musik ID, Gwasanaeth Argymell Cerddoriaeth CY, Tseirbhís Molta Ceoil GA, Tsjinst Foar Oanbefelling Fan Muzyk FY, Ọrụ Nkwanye Egwu IG, Inkonzo Yokucebisa Ngomculo XH, Tónlistarmælaþjónusta IS, מוזיק רעקאַמאַנדיישאַן דינסט YI, Il Servizio Di Raccomandazione Musicale IT, Iṣẹ Iṣeduro Orin YO, 音楽推薦サービス JA, Insiza Yokunconywa Komculo ZU, Layanan Rekomendasi Musik JV, 音樂推薦服務 ZY, ಸಂಗೀತ ಶಿಫಾರಸು ಸೇವೆ KN, Ang Serbisyo Sa Rekomendasyon Sa Musika CEB, Музыкалық Ұсыныс Қызметі KK, ʻ Servicelelo Lawelawe Loiloi HAW, សេវាកម្មណែនាំតន្រ្តី KM, Suab Paj Nruag Lus Pom Zoo Muab Kev Pabcuam HMN, Serivisi Yo Gutanga Imiziki RW, Музыкалык Сунуштоо Кызматы KY, 음악 추천 서비스 KO, Karûbarê Pêşniyara Mûzîkî KU, Musica LA, Musek Empfehlungsservice LB, ການບໍລິການແນະ ນຳ ເພັງ LO, Muzikos Rekomendacijų Paslauga LT, Mūzikas Ieteikumu Pakalpojums LV, Услуга За Препорака На Музика MK, Ny Serivisy Fanolorana Ny Mozika MG, Perkhidmatan Cadangan Muzik MS, സംഗീത ശുപാർശ സേവനം ML, Servizz Ta 'rakkomandazzjoni Mużikali MT, Ko Te Ratonga Tūtohutanga Puoro MI, संगीत शिफारस सेवा MR.
Leverage our ready-to-publish articles on Musiac, offered in a range of languages: Spanish, Italian, Dutch, German, English, Korean, Japanese, Russian, French, Portuguese, Turkish, Arabic (Standard), Indonesian, Chinese (Mandarin) and Hindi.
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.
Algorithm autocracy, Ethical interface, Information architecture, Data visualization, User empowerment, Collaborative filtering
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.
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.
Musiac was a one year project done in 2018, Detroit.
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.
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.
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.
All materials required in this project doesn't need attributions. Licenses are attached in the documentation appendix.
Musiac Music Recommendation Service has been a Silver winner in the Interface, Interaction and User Experience Design award category in the year 2019 organized by the prestigious A' Design Award & Competition. The Silver A' Design Award celebrates top-tier designs that embody excellence and innovation. This award acknowledges creations that are not only aesthetically pleasing but also highly functional, reflecting the designer's deep understanding and skill. Silver A' Design Award recipients are recognized for their contribution to raising industry standards and advancing the practice of design. Their work often incorporates original innovations and elicits a strong emotional response, making a notable impact on the improvement of everyday life.
Chia-Min Lin was recognized with the coveted Silver A' Design Award in 2020, a testament to excellence of their work Musiac Music Recommendation Service.
Discover Chia-Min Lin's journey through our press releases, available for all press members and journalists to use without restrictions. Journalists, gain instant access to 1 press releases today.
Musiac, a desktop application designed by Chia-Min Lin in Detroit in 2018, is a groundbreaking music recommendation service that challenges traditional design thinking and empowers users to explore new musical territories.
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