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Hello,

 

I am working on a school project in which I would like to use gracenote's mood classifications to recomend music which will help a user to exercise more often.

In order to achieve this, we would like to be able to interpret the moods in terms of how they relate to one another. Some googling around suggests that the 100 level 2 moods correspond to a 10x10 grid with the x axis ranging from calm to energetic and the y axis ranging from dark to positive.

We would like to be able to quickly relate a mood's text identifier or id to it's location in this grid so that we can treat the moods as a 2D spectrum rather than completely independent values. I have found a grid describing the mood taxonomy on page 18 of the presentation found here, http://www.slideshare.net/swissnexSF/peter-dimaria-and-chingwei-chen-largescale-machine-listening-and-automatic-mood-labeling-for-music-discovery-in-consumer-applications.

My question is if there is an easy way to convert the 2 level mood ID to its coordinates in this grid. If I could access a list of mood ID's formatted in this grid, that would be a great help, or if the mood's grid location is somehow encoded into it's ID, that would be cool. Otherwise, I will probably have to use the image linked above and manually create a dictionary mapping mood texts to their coordinates.

Thanks for any help!

I have solved this myself. Here are the grid coordinates of moods as a dict, if anyone needs the same.

{'Pastoral / Serene':[0,0], 'Delicate / Tranquil':[0,1], 'Hopeful / Breezy':[0,2], 'Cheerful / Playful':[0,3], 'Carefree Pop':[0,4], 'Party / Fun':[0,5], 'Showy /      Rousing':[0,6], 'Lusty / Jaunty':[0,7], 'Loud Celebratory':[0,8], 'Euphoric Energy':[0,9],

 'Reverent / Healing':[1,0], 'Quiet / Introspective':[1,1], 'Friendly':[1,2], 'Charming / Easygoing':[1,3], 'Soulful / Easygoing':[1,4], 'Happy / Soulful':[1,5], 'Playful /          Swingin':[1,6], 'Exuberant / Festive':[1,7], 'Upbeat Pop Groove':[1,8], 'Happy Excitement':[1,9],

 'Refined / Mannered':[2,0], 'Awakening / Stately':[2,1], 'Sweet / Sincere':[2,2], 'Heartfelt Passion':[2,3], 'Strong / Stable':[2,4], 'Powerful / Heroic':[2,5], 'Invigorating /     Joyous':[2,6], 'Jubilant / Soulful':[2,7], 'Ramshackle / Rollicking':[2,8], 'Wild / Rowdy':[2,9],

 'Romantic / Lyrical':[3,0], 'Light Groovy':[3,1], 'Dramatic / Romantic':[3,2], 'Lush / Romantic':[3,3], 'Dramatic Emotion':[3,4], 'Idealistic / Stirring':[3,5], 'Focused            Sparkling':[3,6], 'Triumphant / Rousing':[3,7], 'Confident / Tough':[3,8], 'Driving Dark Groove':[3,9],

 'Tender / Sincere':[4,0], 'Gentle Bittersweet':[4,1], 'Suave / Sultry':[4,2], 'Dark Playful':[4,3], 'Soft Soulful':[4,4], 'Sensual Groove':[4,5], 'Dark Sparkling Lyrical':[4,6],    'Fiery Groove':[4,7], 'Arousing Groove':[4,8], 'Heavy Beat':[4,9],

 'Lyrical Sentimental':[5,0], 'Cool Melancholy':[5,1], 'Intimate Bittersweet':[5,2], 'Smoky / Romantic':[5,3], 'Dreamy Pulse':[5,4], 'Intimate Passionate':[5,5], 'Rhythm Energetic': [5,6], 'Abstract Groove':[5,7], 'Edgy / Sexy':[5,8], 'Abstract Beat':[5,9],

 'Mysterious / Dreamy':[6,0], 'Light Melancholy':[6,1], 'Casual Groove':[6,2], 'Wary / Defiant':[6,3], 'Bittersweet Pop':[6,4], 'Energetic Yearning':[6,5], 'Dark Pop':[6,6], 'Dark   Pop Intensity':[6,7], 'Heavy Brooding':[6,8], 'Hard Positive Excitement':[6,9],

 'Wistful / Forlorn':[7,0], 'Sad / Soulful':[7,1], 'Cool Confidence':[7,2], 'Dark Groovy':[7,3], 'Sensitive / Exploring':[7,4], 'Energetic Dreamy':[7,5], 'Dark Urgent':[7,6],        'Energetic Anxious':[7,7], 'Attitude / Defiant':[7,8], 'Hard Dark Excitement':[7,9],

 'Solemn / Spiritual':[8,0], 'Enigmatic / Mysterious':[8,1], 'Sober / Determined':[8,2], 'Strumming Yearning':[8,3], 'Melodramatic':[8,4], 'Hypnotic Rhythm':[8,5], 'Evocative /      Intriguing':[8,6], 'Energetic Melancholy':[8,7], 'Dark Hard Beat':[8,8], 'Heavy Triumphant':[8,9],

 'Dark Cosmic':[9,0], 'Creepy / Ominous':[9,1], 'Depressed / Lonely':[9,2], 'Gritty / Soulful':[9,3], 'Serious / Cerebral':[9,4], 'Thrilling':[9,5], 'Dreamy Brooding':[9,6],         'Alienated / Brooding':[9,7], 'Chaotic / Intense':[9,8], 'Aggressive Power':[9,9]}

 

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An analysis of the interpretation of indicative/subjunctive contrasts in embedded clauses is pursued here that, rather than attaching rigid meanings to each mood, views mood shifts as the overt marking of a change in the model for the evaluation of the proposition or property expressed by the embedded clause. From this perspective, mood morphology conveys information about model flow in discourse, which can be determined by a variety of factors ranging from lexical meaning of embedding predicates to different aspects of discourse interpretation and context change. The proposal identifies and analyzes the parameters that induce model shift in subordinated domains. Macys Insite This allows us to distinguish core cases of subjunctive selection from more peripheral ones, both within a language and crosslinguistically, and it also provides us with an explanation for several empirical problems that a rigid interpetation of mood leaves unresolved. WalmartOne The analysis offered concentrates on mood distribution in Catalan and Spanish.

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