(Group Members: Amit Sharma, Ambika Na, Deepa Vyasabhat, Jaspreet Singh)
There are millions of songs out there. However, only a handful of them can be considered popular. Can we build a system that can predict whether a song can be popular based on it's lyrics? Using advanced NLP and ML techniques, we think this is possible. This tool would have a significant impact on aspiring song writers.
The project is based on natural language processing over the existing lyrical dataset of over 5000+ popular songs and then using machine learning algorithms to generate a prediction model for guessing popularity of new songs based on keywords extracted from the lyrical dataset. The prediction model will be based upon the data extracted from already hit songs and will try to estimate the popularity of new songs based upon song’s length, repetition of words, usage of pop culture keywords.
We have utilized an open source dataset from Kaggle website, consisting of 5000+ popular hit songs from various genres and timescale. The data consists of many variables like performing artist, genre, total word length, year of release. Through, natural language processing we are extracting key features to prepare our dataset which will be used by machine learning algorithms. Some of the key features in our cleaned dataset are "most often used words", "average length" etc. We have used knn algorithm, random forest, linear regression, logistic regression to generate a prediction model which will conclude whether a provided lyrics could be popular or not.
We have developed a website for aspiring song writers. They can register to our system and can view their past searched lyrics. We are also providing visualisation to users based on the cleaned dataset which will help users in deciding which words to include while writing lyrics. It will also help them in gaining insights into behavior and structure of popular songs.
This tool can be used in the music industry by artists associated with it ranging from lyricists, singers and music directors.
Input string 1:
"Spent 24 hours I need more hours with you You spent the weekend Getting even, ooh ooh We spent the late nights Making things right, between us But now it's all good baby Roll that Backwood baby And play me close 'Cause girls like you Run around with guys like me 'Til sundown, when I come through I need a girl like you, yeah yeah Girls like you Love fun, yeah me too What I want when I come through I need a girl like you, yeah yeah Yeah yeah yeah Yeah yeah yeah I need a girl like you, yeah yeah Yeah yeah yeah Yeah yeah yeah I need a girl like you, yeah yeah I spent last night On the last flight to you Took a whole day up Trying to get way up, ooh ooh We spent the daylight Trying to make things right between us And now it's all good baby Roll that Backwood baby And play me close 'Cause girls like you Run around with guys like me 'Til sundown, when I come through I need a girl like you, yeah yeah Girls like you Love fun, yeah me too What I want when I come through I need a girl like you, yeah yeah Yeah yeah yeah Yeah yeah yeah I need a girl like you, yeah yeah Yeah yeah yeah Yeah yeah yeah I need a girl like you, yeah yeah I need a girl like you, yeah yeah I need a girl like you Maybe it's 6:45 Maybe I'm barely alive Maybe you've taken my shit for the last time, yeah Maybe I know that I'm drunk Maybe I know you're the one Maybe I'm thinking it's better if you drive 'Cause girls like you Run around with guys like me 'Til sundown, when I come through I need a girl like you, yeah yeah 'Cause girls like you Run around with guys like me 'Til sundown, when I come through I need a girl like you, yeah yeah Girls like you Love fun, yeah me too What I want when I come through I need a girl like you, yeah yeah Yeah yeah yeah Yeah yeah yeah I need a girl like you, yeah yeah Yeah yeah yeah Yeah yeah yeah I need a girl like you"
Output 1:
Input string 2:
an American multinational conglomerate technology company based in Seattle, with 750,000 employees.[8] It focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence. It is considered one of the Big Four tech companies, along with Google, Apple, and Microsoft.[9][10][11] It has been referred to as "one of the most influential economic and cultural forces in the world."[12] Amazon is known for its disruption of well-established industries through technological innovation and mass scale.[13][14][15] It is the world's largest online marketplace, AI assistant provider, and cloud computing platform[16] as measured by revenue and market capitalization.[17] Amazon is the largest Internet company by revenue in the world.[18] It is the second largest private employer in the United States[19] and one of the world's most valuable companies. Amazon was founded by Jeff Bezos in Bellevue, Washington, in July 1994. The company initially started as an online marketplace for books but later expanded to sell electronics, software, video games, apparel, furniture, food, toys, and jewelry. In 2015, Amazon surpassed Walmart as the most valuable retailer in the United States by market capitalization.[20] In 2017, Amazon acquired Whole Foods Market for US$13.4 billion, which vastly increased Amazon's presence as a brick-and-mortar retailer.[21] In 2018, Bezos announced that its two-day delivery service, Amazon Prime, had surpassed 100 million subscribers worldwide.
Output 2:
Input String 4:
I was sittin' on a bar stool In a barbecue joint in Tennessee When this old boy walked in And he sat right down next to me I could tell he'd been through some hard times 'Cause there were tear stains on his old shirt And he said, you wanna know what you get When you play a country song backwards You get your house back You get your dog back You get your best friend Jack back You get your truck back You get your hair back You get your first and second jobs back Your front porch swing Your bling, bling, bling and a diamond ring You get your farm, and the barn And the boat, and the Harley And that old black cat named Charlie It sounds a little crazy A little scattered and absurd But that's what you get When you play a country song backwards Well, I never heard it said quite like that It hit me in the face 'cause that's where I'm at I almost fell flat out on the floor He said, wait a minute, that's not all There's even more You get your mind back You get your nerves back Your achy breaky heart You get your pride back You get your life back You get your first real love back You get your big screen TV, a DVD And a washing machine You get the pond, and the lawn The breaker, and the mower You go back where you don't know her It sounds a little crazy A little scattered and absurd But that's what you get When you play a country song backwards Oh play that song! We sat there and talked About how it would be If we could turn it all around And go back T-I-M-E You get your house back You get your dog back You get your best friend Jack back You get your truck back You get your hair back You get your first and second job back Your front porch swing Your bling, bling, bling and a diamond ring You get your farm, and the barn And the boat, and the Harley And that old black cat named Charlie You get your mind back You get your nerves back Your achy breaky heart You get your pride back You get your life back You get your first real love back You get your big screen TV, a DVD And a washing machine You get the pond, and the lawn The breaker, and the mower You go back when life was slower It sounds a little crazy A little scattered and absurd But that's what you get When you play a country song backwards
Output 4:
Input String 5:
Yeah, you got that yummy, yum That yummy, yum That yummy, yummy Yeah, you got that yummy, yum That yummy, yum That yummy, yummy Say the word, on my way Yeah babe, yeah babe, yeah babe Any night, any day Say the word, on my way Yeah babe, yeah babe, yeah babe In the morning or late Say the word, on my way Bona fide stallion You ain't in no stable, no, you stay on the run Ain't on the side, you're number one Yeah, every time I come around, you get it done Fifty-fifty, love the way you split it Hunnid racks, help me spend it, babe Light a match, get litty, babe That jet set, watch the sunset kinda, yeah, yeah Rollin' eyes back in my head, make my toes curl, yeah, yeah Yeah, you got that yummy, yum That yummy, yum That yummy, yummy Yeah, you got that yummy, yum That yummy, yum That yummy, yummy Say the word, on my way Yeah babe, yeah babe, yeah babe Any night, any day Say the word, on my way Yeah babe, yeah babe, yeah babe In the morning or late Say the word, on my way Standing up, keep me on the rise Lost control of myself, I'm compromised You're incriminating, no disguise And you ain't never running low on supplies Fifty-fifty, love the way you split it Hunnid racks, help me spend it, babe Light a match, get litty, babe That jet set, watch the sunset kinda, yeah, yeah Rollin' eyes back in my head, make my toes curl, yeah, yeah Yeah, you got that yummy, yum That yummy, yum That yummy, yummy (and you stay flexing on me) Yeah, you got that yummy, yum That yummy, yum (yeah) That yummy, yummy Say the word, on my way Yeah babe, yeah babe, yeah babe (yeah babe) Any night, any day Say the word, on my way Yeah babe, yeah babe, yeah babe (yeah babe) In the morning or late Say the word, on my way Hop in the Lambo, I'm on my way Drew House slippers on with a smile on my face I'm elated that you are my lady You got the yum, yum, yum, yum You got the yum, yum, yum, whoa Whoa-ooh Yeah, you got that yummy, yum That yummy, yum That yummy, yummy Yeah, you got that yummy, yum That yummy, yum That yummy, yummy Say the word, on my way Yeah babe, yeah babe, yeah babe (yeah babe) Any night, any day Say the word, on my way Yeah babe, yeah babe, yeah babe (yeah babe) In the morning or late Say the word, on my way
Output 5:
Link of architecture diagram: https://github.com/SJSUSpring2020-CMPE272/Lyrics-Analyser/blob/master/Architecture/architecture.png
Frontend: React, AntDesign CSS ,React-viz, D3-cloud
Backend: NodeJS, express, Python, mongoDB
Libararies : numpy , scikit.learn , Pandas
Deployment: Dockers/containers running on Amazon EC2 instances Load balanced with network ELB.
Dataset: open source dataset from Kaggle website, consisting of 5000+ popular hit songs