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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Available for Journalists: An in-depth interview with Chia-Min Lin, around 1029 words, ready for complimentary use in your articles. Download it today. Access Chia-Min Lin Interview Now.
Availability alert: Press releases for Musiac in languages including English.
Proudly offering Musiac project translations in several languages: Musiekaanbevelingsdiens AF, Shërbimi I Rekomandimit Të Muzikës SQ, የሙዚቃ የምክር አገልግሎት AM, خدمة التوصية بالموسيقى AR, Երաժշտության Առաջարկությունների Ծառայությունը HY, Musiqi Tövsiyə Xidməti AZ, Musika Gomendio Zerbitzua EU, Паслуга Рэкамендацыі Музыкі BE, সংগীত প্রস্তাবনা পরিষেবা BN, Glazbena Preporuka Usluga BS, Услугата За Препоръчване На Музика BG, ဂီတထောက်ခံချက်ဝန်ဆောင်မှု MY, El Servei De Recomanacions Musicals CA, Ntchito Yovomerezera Nyimbo NY, 音乐推荐服务 ZH, U Serviziu Di Raccomandazione Di Musica CO, Glazbena Preporuka Usluga HR, Hudební Doporučení CS, Musikanbefalingstjeneste DA, Muziekaanbevelingsservice NL, Muzika Rekomendoservo EO, Muusikasoovitusteenus ET, Musiikkisuosituspalvelu FI, Le Service De Recommandation Musicale FR, O Servizo De Recomendacións Musicais GL, მუსიკალური სარეკომენდაციო მომსახურება KA, Musikempfehlungsdienst DE, Η Υπηρεσία Σύστασης Μουσικής EL, સંગીત ભલામણ સેવા GU, Sèvis Rekòmandasyon Mizik HT, Sabis Na Bayar Da Shawarar Kiɗa HA, שירות המלצות מוזיקה HE, संगीत सिफारिश सेवा HI, A Zenei Ajánlás Szolgáltatás HU, Layanan Rekomendasi Musik ID, Tseirbhís Molta Ceoil GA, Ọrụ Nkwanye Egwu IG, Tónlistarmælaþjónusta IS, Il Servizio Di Raccomandazione Musicale IT, 音楽推薦サービス JA, Layanan Rekomendasi Musik JV, ಸಂಗೀತ ಶಿಫಾರಸು ಸೇವೆ KN, Музыкалық Ұсыныс Қызметі KK, សេវាកម្មណែនាំតន្រ្តី KM, 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, Хөгжмийн Зөвлөмж Үйлчилгээ MN, संगीत सिफारिश सेवा NE, Musikkanbefalingstjeneste NO, ସଂଗୀତ ସୁପାରିଶ ସେବା OR, ਸੰਗੀਤ ਦੀ ਸਿਫਾਰਸ਼ ਸੇਵਾ PA, سرویس توصیه موسیقی FA, Usługa Rekomendacji Muzycznych PL, د میوزیک سپارښتنې خدمت PS, O Serviço De Recomendação De Música PT, Serviciul De Recomandare Muzicală RO, Сервис Музыкальных Рекомендаций RU, موسيقي جي سفارش سروس SD, Musika Fautuaga Auaunaga SM, Музичка Препорука Услуга SR, Seirbheis Moladh Ciùil GD, Mumhanzi Kukurudzira Sevhisi SN, සංගීත නිර්දේශ සේවාව SI, Služba Hudobných Odporúčaní SK, Glasbena Priporočila Storitev SL, Adeegga Talo Bixinta Muusikada SO, Tšebeletso Ea Litlhahiso Tsa Mmino ST, El Servicio De Recomendación Musical ES, Jasa Rekomendasi Musik SU, Huduma Ya Kupendekeza Muziki SW, Musikrekommendationstjänst SV, இசை பரிந்துரை சேவை TA, సంగీత సిఫార్సు సేవ TE, Хадамоти Тавсиядиҳии Мусиқӣ TG, บริการแนะนำเพลง TH, Aýdym-Saz Maslahat Beriş Hyzmaty TK, Ang Serbisyo Sa Rekomendasyon Ng Musika TL, Müzik Öneri Hizmeti TR, Музыка Тәкъдим Итү Хезмәте TT, مۇزىكا تەۋسىيە مۇلازىمىتى UG, Послуга Музичних Рекомендацій UK, موسیقی کی سفارش کی خدمت UR, Musiqiy Tavsiyanoma Xizmati UZ, Dịch Vụ Giới Thiệu Âm Nhạc VI, Gwasanaeth Argymell Cerddoriaeth CY, Tsjinst Foar Oanbefelling Fan Muzyk FY, Inkonzo Yokucebisa Ngomculo XH, מוזיק רעקאַמאַנדיישאַן דינסט YI, Iṣẹ Iṣeduro Orin YO, Insiza Yokunconywa Komculo ZU, 音樂推薦服務 ZY, Ang Serbisyo Sa Rekomendasyon Sa Musika CEB, ʻ Servicelelo Lawelawe Loiloi HAW, Suab Paj Nruag Lus Pom Zoo Muab Kev Pabcuam HMN, Music Recommendation Service EN, tailored for your needs.
Leverage our ready-to-publish articles on Musiac, offered in a range of languages: Spanish, English, French, Portuguese, Turkish, Arabic (Standard), Indonesian, Chinese (Mandarin), Japanese, Russian, Italian, Dutch, German, Korean 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.
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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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