Morgen is a smart speaker that serves as a personal DJ by learning the musical taste of the user. Simply touching to “like” and swipe to “dislike” and the speaker will recommend music accordingly.
Shenzhen Trendwoo Tech. Co., Ltd., China
Team Lead: Wang Yang
Design: Ye Liangwen, Yu Xueliang, Wang Hui, Lin Jinchun
Morgen, with the latest application of Internet of Things (IoT), combines a cloud service with a stylishly designed portable speaker to create a better personal music experience. People are now in evermore need of different resources to discover more music. Some platforms like Pandora may provide music personalisation services but they only stream online, which can be limiting when the Internet access is not available. Therefore, Morgen emerges as a new smart portable speaker that learns the user’s taste in music and recommends new music accordingly that can be played offline.
Morgan is equipped with a cloud service so that users can listen to music in HiFi quality from a large and unlimited cloud database. Powered by Internet of Things, different channels are pre-set for different music genres: Jazz, Pop, Rock, Country, Classical, etc. It is accompanied by an application for smartphones so that users can set up the channels, check the battery status of the speaker and view the song titles and artist information.
Morgan’s “Smart Recommendation” function remembers the user’s musical taste. The user only has to make two different “gestures” on the touch control pad – swipe to “dislike” the song or touch to “like” the song. Morgan recommends songs similar to the ones the users have liked. Morgan also caches songs online to allow for offline music enjoyment in HiFi quality.
Morgan has an elegant and stylish exterior design comprising an aluminium frame, fabric mesh, touch-control function, and a rotary volume and channel control. Over 4000 songs are pre-loaded into different channels for each new Morgen device. To operate, turn on the speaker, select the genre channel of choice, begin listening to music and while doing so, start using “gestures” to identify songs according to “like” and “dislike”. The longer the usage and more frequently “gestures” are used, the sooner can Morgan turn into an accurate music personalisation DJ.