Found 1128 bookmarks
Newest
Songza Brings ‘Playlists for Everything’ to iPhone & Android
Songza Brings ‘Playlists for Everything’ to iPhone & Android
Songza App Key Features:     Social music discovery – Log into Songza with your Facebook account to serendipitously discover new playlists that your friends are listening to or creating, and to view your friends’ music collections.     Expert-curated discovery – Easily access the perfect playlist organized by a wide range of activities, genres, moods, decades and culture. For example, the activities category helps you find the perfect soundtrack for everything from hosting a dinner party, to coding software, to barbequing.     Cloud-based music collection – Save your favorite playlists to your personal music collection. Collections can be shared with friends, organized by era, activity, mood, genre or any other categorization and accessed from anywhere.
Songza features over 75,000 playlists created by people – including music experts, celebrities, artists and record labels.
Any Songza user can create their own playlist using the Songza.com website and share it with the community, choosing from Songza’s library of over 14.5 million songs.
·prweb.com·
Songza Brings ‘Playlists for Everything’ to iPhone & Android
Songza’s Co-Founder Tells Us What Makes Their Playlists So Dang Good
Songza’s Co-Founder Tells Us What Makes Their Playlists So Dang Good
Anchoring the offering around brilliant playlists as part of a feature called Concierge.
The Concierge service is time-sensitive, season-specific, and is often eerily on point.
But how do they do it? A playlist like “Being Pretentious” just has to have been dreamed up by a real-life human, not an algorithm. Right? And how do they know that on a Friday afternoon, a playlist centered around burning through your inbox should kick off with the Backstreet Boys’ “Everybody (Backstreet’s Back)”?
So the process begins with our editorial team mapping out all of life’s moments that can be improved with a great soundtrack.
Within each of those moments, the team then maps out each of the different types of music that might appeal to different types of music fans in those moments.
For each of those types of music, playlists are then handcrafted by our team of dozens of music experts, song by song.
There are hundreds of ‘moments’ mapped out, and new ones are created all the time. We use a combination of a little intuition and a lot of data to help us anticipate what moment a given user will be in.
It starts—and ends—with 100% expert, human curation. What allows our user experience to scale is that each of these handcrafted playlists are then algorithmically matched to the right person, in the right moment.
·stylecaster.com·
Songza’s Co-Founder Tells Us What Makes Their Playlists So Dang Good
EDA | Creating Our Own Spotify Playlist Recommendation Models
EDA | Creating Our Own Spotify Playlist Recommendation Models
ACOUSTICNESSfloatA confidence measure from 0.0 to 1.0 of whether the track is acoustic. 1.0 represents high confidence the track is acoustic.DANCEABILITYfloatDanceability describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. A value of 0.0 is least danceable and 1.0 is most danceable.ENERGYfloatEnergy is a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity. Typically, energetic tracks feel fast, loud, and noisy. For example, death metal has high energy, while a Bach prelude scores low on the scale. Perceptual features contributing to this attribute include dynamic range, perceived loudness, timbre, onset rate, and general entropy.INSTRUMENTALNESSfloatPredicts whether a track contains no vocals. “Ooh” and “aah” sounds are treated as instrumental in this context. Rap or spoken word tracks are clearly “vocal”. The closer the instrumentalness value is to 1.0, the greater likelihood the track contains no vocal content. Values above 0.5 are intended to represent instrumental tracks, but confidence is higher as the value approaches 1.0.LIVENESSfloatDetects the presence of an audience in the recording. Higher liveness values represent an increased probability that the track was performed live. A value above 0.8 provides strong likelihood that the track is live.LOUDNESSfloatThe overall loudness of a track in decibels (dB). Loudness values are averaged across the entire track and are useful for comparing relative loudness of tracks. Loudness is the quality of a sound that is the primary psychological correlate of physical strength (amplitude). Values typical range between -60 and 0 db.SPEECHINESSfloatSpeechiness detects the presence of spoken words in a track. The more exclusively speech-like the recording (e.g. talk show, audio book, poetry), the closer to 1.0 the attribute value. Values above 0.66 describe tracks that are probably made entirely of spoken words. Values between 0.33 and 0.66 describe tracks that may contain both music and speech, either in sections or layered, including such cases as rap music. Values below 0.33 most likely represent music and other non-speech-like tracks.VALENCEfloatA measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry).TEMPOfloatThe overall estimated tempo of a track in beats per minute (BPM). In musical terminology, tempo is the speed or pace of a given piece and derives directly from the average beat duration.KEYintThe estimated overall key of the track. Integers map to pitches using standard Pitch Class notation . E.g. 0 = C, 1 = C♯/D♭, 2 = D, and so on. If no key was detected, the value is -1.MODEintMode indicates the modality (major or minor) of a track, the type of scale from which its melodic content is derived. Major is represented by 1 and minor is 0.
·cs109group33.wixsite.com·
EDA | Creating Our Own Spotify Playlist Recommendation Models