Music track exploration and playlist creation

Abstract

The invention enables music tracks in a playlist to be explored using a unique music genogram data format. The invention further enables a user to map an emotional trajectory on the emotion wheel as a basis for the generation of the playlist with music tracks. The invention provides for a unique visualization of the playlist using the emotional wheel representation. A user will be given the option to specify an initial mood and a destination mood. The trajectory between the initial mood and the destination mood may be steered through the emotions falling in-between. The thus obtained mood trajectory is then populated by music tracks to form a playlist.

1 . A computer-implemented method for exploring music tracks, the method comprising:
 displaying a graphical representation of a first music genogram of a first music track, the first music genogram having a music genogram data structure for defining the music genogram;   receiving a first exploration input indicating a selection of one of the tags in one of the sections; and   if the first exploration input indicates a pro-tag, displaying a first link to a second music genogram of a second music track, and/or if the pro-tag comprises two or more micro-pro tags, displaying a graphical representation of the decomposition of the pro-tag and a second link to a third music genogram of a third music track for each of the micro-pro tags, wherein the music genogram data structure comprises:   sub-segment data identifying one or more sub-segments to define a decomposition in time of a music track, each sub-segment having a start time and an end time; and   band data identifying one or more bands to define a decomposition for the time length of the music track, wherein a cross section of a sub-segment and a band forms a section, the music genogram data structure further comprising:   tag data identifying one or more tags in one or more sections, wherein a tag is one of:   a deceptive tag to indicate a surprising effect;   a pro-tag to identify a starting point for an exploration, using a graphical user interface, of another music genogram based on similarities;   a sudden change tag to indicate a substantial change in scale, pitch or tempo;   a hook tag to identify a unique sound feature in the music track; or   a micro-pro tag to enable a decomposition of the pro-tag.   
     
     
         2 . The method according to  claim 1 , wherein each section is subdivided in two or more subsections and wherein the tag data identifies the one or more tags in a subsection. 
     
     
         3 . The method according to  claim 1 , wherein each sub-segment is one of an intro part, a main vocals part, an instrumental part, a stanza vocals part or a coda part, and wherein each band is one of a beat band, a tune band or a special tune band. 
     
     
         4 . The method according to  claim 1 , wherein the first music track is one of two or more media items in a playlist, wherein each media item comprises meta-data indicating one or more characteristics of the media item, the method further comprising:
 displaying a graphical representation of an emotional wheel, the emotional wheel being a two dimensional Cartesian coordinate system based model for classification of emotions wherein emotions are located at predefined coordinates;   receiving a first input indicating a starting point of a mood trajectory in the emotional wheel, the starting point corresponding to an initial mood at one of the coordinates;   receiving a second input indicating an end point of the mood trajectory in the emotional wheel, the end point corresponding to a destination mood at one of the coordinates;   defining the mood trajectory by connecting the starting point to the end point via one or more intermediate points, the intermediate points corresponding to one or more intermediate moods;   displaying a graphical representation of the mood trajectory in the graphical representation of the emotional wheel;   selecting the media items by searching in the meta-data for emotion characteristics or mood characteristics that match the initial mood, the intermediate moods and the destination mood, respectively; and   creating the playlist of media items in an order from initial mood to destination mood.   
     
     
         5 . The method according to  claim 4 , wherein the starting point, the end point and the intermediate points are predefined to form a predefined mood trajectory, the method further comprising receiving a third input to select the predefined mood trajectory. 
     
     
         6 . The method according to  claim 4 , further comprising:
 receiving a fourth input indicating a change in coordinates of one or more of the intermediate points; and   redefining the mood trajectory by connecting the starting point to the end point via the changed intermediate points.   
     
     
         7 . The method according to  claim 4 , further comprising:
 calculating a first series of intersecting circular sections along the mood trajectory, wherein each circular section in the first series has a center point on the mood trajectory; and   calculating a second series of circular sections, wherein each circular section in the second series has a center point at an intersection point of two circular sections in the first series,   wherein the first series of circular sections and the second series of circular sections together form an area around the mood trajectory,   
       or further comprising:
 calculating an area around the trajectory using a probabilistic distribution function or distance function to form a regular or irregular shaped area around the mood trajectory, and wherein selecting the media items by searching in the meta-data for emotion characteristics or mood characteristics that match the initial mood, the destination mood, and moods with coordinates within the area around the trajectory, respectively. 
 
     
     
         8 . The method according to  claim 4 , further comprising receiving a fifth input indicating one or more media characteristics and/or receiving a sixth input indicating a maximum number of media items in the playlist and/or a maximum time-length of the playlist, and wherein the selecting of the media items is restricted to the one or more further media characteristics and/or the maximum number of media items and/or the maximum time-length. 
     
     
         9 . The method according to  claim 4 , further comprising receiving a seventh input indicating a weight factor for one or more of the starting point, the intermediate points and the end point, and wherein in the playlist the number of media items selected for the starting point, the intermediate point or the end point for which the weight factor is received is dependent on the value of the weight factor. 
     
     
         10 . The method according to  claim 9 , further comprising displaying in the graphical representation of the mood trajectory one or more resized points having a size indicating a probability that media items are selected at the coordinates of the resized points. 
     
     
         11 . The method according to  claim 4 , further comprising storing shock data comprising an indication of a media shock applied by a user to a particular media item in the playlist and an indication of a relative position of the particular media item in the playlist or mood trajectory,
 and wherein the selecting of the media items uses the stored shock data to influence the probability that the particular media item is selected.   
     
     
         12 . A computer program product comprising software code portions configured for, when run on a computer, executing the method steps according to  claim 1 .