Researchers developed a machine-learning algorithm that learned to rap
The rapping algorithm was quantitatively evaluated with two measures. First, the prediction performance was evaluated by measuring how well the algorithm predicts the next line of an existing rap song. This it can do surprisingly well.
- An 82% accuracy was achieved for separating the true next line from a randomly chosen line, says researcher Eric Malmi.
Second, a rhyme density measure was introduced and showed that DeepBeat, an algorithm for rap lyrics generation, outperforms the top human rappers by 21 % in terms of length and frequency of the rhymes in the produced lyrics.
The validity of the rhyme density measure was assessed by conducting a human experiment which showed that the measure correlates with a rapper's own notion of technically skilled lyrics.
Here is one DeepBeat generated on the topic of love:
For a chance at romance I would love to enhance
But everything I love has turned to a tedious task
One day we gonna have to leave our love in the past
I love my fans but no one ever puts a grasp
I love you momma I love my momma – I love you momma
And I would love to have a thing like you on my team you take care
I love it when it’s sunny Sonny girl you could be my Cher
I’m in a love affair I can’t share it ain’t fair
Haha I’m just playin’ ladies you know I love you.
I know my love is true and I know you love me too
Girl I’m down for whatever cause my love is true
This one goes to my man old dirty one love we be swigging brew
My brother I love you Be encouraged man And just know
When you done let me know cause my love make you be like WHOA
If I can’t do it for the love then do it I won’t
All I know is I love you too much to walk away though
Future work could focus on refining storylines, and ultimately integrating a speech synthesizer that would give DeepBeat also a voice.
Researchers Eric Malmi and Pyry Takala, professors Tapani Raiko and Aristides Gionis from the Department of Computer Science at the Aalto University and professor Hannu Toivonen from the University of Helsinki and HIIT developed a machine-learning algorithm that learned to rap. To train the machine-learning algorithm, the researchers began with a database of over 10,000 songs from more than 100 rap artists.
More information:
Eric Malmi, eric.malmi@aalto.fi
DopeLearning: A Computational Approach to Rap Lyrics Generation
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