Spectrum is an AI that uses machine learning to generate Rap song lyrics

Overview

Contributors Forks Stargazers Issues MIT License Open In Colab


Spectrum

Spectrum is an AI that uses deep learning to generate rap song lyrics.

View Demo
Report Bug
Request Feature
Open In Colab

About The Project

Spectrum is an AI that uses deep learning to generate rap song lyrics.

Built With

This project is built using Python, Tensorflow, and Flask.

Getting Started

Installation

# clone the repo
git clone https://github.com/YigitGunduc/Spectrum.git

# install requirements
pip install -r requirements.txt

Training

# navigate to the Spectrum/AI folder 
cd Spectrum/AI

# pass verbose, epochs, save_at arguments and run train.py 
python3 train.py -h, --help  --epochs EPOCHS --save_at SAVE_AT --verbose VERBOSE --rnn_neurons RNN_NEURONS
             --embed_dim EMBED_DIM --dropout DROPOUT --num_layers NUM_LAYERS --learning_rate LEARNING_RATE

All the arguments are optional if you leave them empty model will construct itself with the default params

Generating Text from Trained Model

Call eval.py from the command line with seed text as an argument

python3 eval.py --seed SEEDTEXT

or

from model import Generator

model = Generator()

model.load_weights('../models/model-5-epochs-256-neurons.h5')

generatedText = model.predict(start_seed=SEED, gen_size=1000)

print(generatedText)
  • If you have tweaked the model's parameters while training initialize the model with the parameters you trained

Running the Web-App Locally

# navigate to the Spectrum folder 
cd Spectrum

# run app.py
python3 app.py

# check out http://0.0.0.0:8080

API

spectrum has a free web API you can send request to it as shown below

import requests 

response = requests.get("https://spectrumapp.herokuapp.com/api/generate/SEEDTEXT")
#raw response
print(response.json())
#cleaned up response
print(response.json()["lyrics"])

Hyperparameters

epochs = 30 
batch size = 128
number of layers = 2(hidden) + 1(output)
number of RNN units = 256
dropout prob = 0.3
embedding dimensions = 64
optimizer = Adam
loss = sparse categorical crossentropy

These hyperparameters are the best that I can found but you have to be careful while dealing with the hyperparameters because this model can over or underfit quite easily and GRUs performs better than LSTMs

Info about model

>>> from model import Generator
>>> model = Generator()
>>> model.load_weights('../models/model-5-epochs-256-neurons.h5')
>>> model.summary()
Model: "sequential"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
embedding (Embedding)        (1, None, 64)             6400      
_________________________________________________________________
gru (GRU)                    (1, None, 256)            247296    
_________________________________________________________________
gru_1 (GRU)                  (1, None, 256)            394752    
_________________________________________________________________
dense (Dense)                (1, None, 100)            25700     
=================================================================
Total params: 674,148
Trainable params: 674,148
Non-trainable params: 0
_________________________________________________________________

>>> model.hyperparams()
Hyper Parameters
+--------------------------+
|rnn_neurons   |        256|
|embed_dim     |         64|
|learning_rate |     0.0001|
|dropout       |        0.3|
|num_layers    |          2|
+--------------------------+
>>>

Roadmap

See the open issues for a list of proposed features (and known issues).

Results

WARNING: There is some offensive language ahead, please stop reading here if you are a sensitive person. The texts below have been generated by Spectrum

Seed : today

Prediction : 

If that don't, yeah
Weint off the music
It's like a fired-enother foar fool straight for an exactly
Nigga why I id my Door Merican muthafucka

Ng answered by need for blazy hard
The family wish fans dishes rolled up
How better just wanna die
Match all about the moment in I glory
Fire is that attention is the flop and pipe those peokin' distriors
Bitch I been hard and I'm like the Scales me and we're going to school like all-off of the allegit to get the bitches
Yeah kinda too legit back into highin'
A year have it would plobably want

And we all bustin' the conscious in the cusfuckers won't ha
Quite warkie and it's blow, and what? I cannot love him,
Alugal Superman, and the revolution likes migh
I ain't still not I uest the neighborhoo
Powers all too bad show, you crite your bac
When I say way too fathom
If you wanna revell, money, where your face we'll blin
Pulf me very, yo, they pull out for taught nothin' off
I pass a with a nigga hang some, pleas
Fuck me now, it's a

======================================================================
Seed : hello

Prediction : 

hellow motherfucker
You wanna talk on the pockets on Harlotom
I'm legit some more than Volumon
Ridicalab knowledge is blessin' some of your honierby man
We just bust the Flud joke with shoulders on the Statue
Lecock it on everybody want your dices to speak
While she speak cents look back to Pops
He was a nigga when I got behind pictures any Lil Sanvanas
Used to in her lady yaught they never had a bitch
He'll break the jird little rappers kill your children is

I'm prayin' back to ready for that bitch just finished And mised to the gamr
Every eyes on and about that getting common
I'm going to attractived with its
I just went by the crowd get the promise to buy the money-a star big down
Can one sall 'em in me tryna get them days that's how I can break the top
Well, that's hug her hands he screaming like a fucking hip-hop but put a Blidze like rhymin'
Yeah I slack like a Job let your cops got a generres
These West of it today flamping this
Black Kuttle crib, said "Ju Conlie, hold up, fuck the

======================================================================
Seed : bestfriend

Prediction : 

bestfriend
Too much time we tonight
The way I know is a please have no self-back when I be for the fucking weed and a game
What the fuck we wanna be working on the streets make it like a stay down the world is from the head of the real brain
Chain don't come back to the grass
My dick is the one to tell you I'm the fuck
So see me we gon' be fans when you had to hear the window you come to the dick when a little cooleng and I was calling what the fuck is it good as the crown
And I'm representing you finally waitin' in your girl
This is the corner with my brother
I'm just a damn door and the real motherfuckers come got the point my shit is the money on the world

I get it then the conscious that's why I cripp
I might take my own shit so let me have a bad bitch
I'm just had and make the fuck is in the single of the window
I think I ain't got the world is all my gone be mine
They ain't like the half the best between my words
And I'm changing with the heads of the speech
Fuck a bunch of best of a fuck

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Official implementation of SynthTIGER (Synthetic Text Image GEneratoR) ICDAR 2021

🐯 SynthTIGER: Synthetic Text Image GEneratoR Official implementation of SynthTIGER | Paper | Datasets Moonbin Yim1, Yoonsik Kim1, Han-cheol Cho1, Sun

Clova AI Research 256 Jan 05, 2023
Repository for MDPGT

MD-PGT Repository for implementing and reproducing the results for the paper MDPGT: Momentum-based Decentralized Policy Gradient Tracking. Available E

Xian Yeow Lee 2 Dec 30, 2021
A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks

SVHNClassifier-PyTorch A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks If

Potter Hsu 182 Jan 03, 2023
The original implementation of TNDM used in the NeurIPS 2021 paper (no longer being updated)

TNDM - Targeted Neural Dynamical Modeling Note: This code is no longer being updated. The official re-implementation can be found at: https://github.c

1 Jul 21, 2022
Automatic tool focused on deriving metallicities of open clusters

metalcode Automatic tool focused on deriving metallicities of open clusters. Based on the method described in Pöhnl & Paunzen (2010, https://ui.adsabs

2 Dec 13, 2021
Implementation of ECCV20 paper: the devil is in classification: a simple framework for long-tail object detection and instance segmentation

Implementation of our ECCV 2020 paper The Devil is in Classification: A Simple Framework for Long-tail Instance Segmentation This repo contains code o

twang 98 Sep 17, 2022
Official implementation for "Low-light Image Enhancement via Breaking Down the Darkness"

Low-light Image Enhancement via Breaking Down the Darkness by Qiming Hu, Xiaojie Guo. 1. Dependencies Python3 PyTorch=1.0 OpenCV-Python, TensorboardX

Qiming Hu 30 Jan 01, 2023
Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite and .pb from .tflite.

tflite2tensorflow Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite and .pb from .tflite. 1. Supported Layers No. TFLite Layer TF

Katsuya Hyodo 214 Dec 29, 2022
Repo público onde postarei meus estudos de Python, buscando aprender por meio do compartilhamento do aprendizado!

Seja bem vindo à minha repo de Estudos em Python 3! Este é um repositório criado por um programador amador que estuda tópicos de finanças, estatística

32 Dec 24, 2022
particle tracking model, works with the ROMS output file(qck.nc, his.nc)

particle-tracking-model-for-ROMS particle tracking model, works with the ROMS output file(qck.nc, his.nc) description this is a 2-dimensional particle

xusheng 1 Jan 11, 2022
Code for "Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation". [AAAI 2021]

Graph Evolving Meta-Learning for Low-resource Medical Dialogue Generation Code to be further cleaned... This repo contains the code of the following p

Shuai Lin 29 Nov 01, 2022
SenseNet is a sensorimotor and touch simulator for deep reinforcement learning research

SenseNet is a sensorimotor and touch simulator for deep reinforcement learning research

59 Feb 25, 2022
A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling

large-scale-ITE-UM-benchmark This repository contains code and data to reproduce the results of the paper "A Large Scale Benchmark for Individual Trea

10 Nov 19, 2022
TransNet V2: Shot Boundary Detection Neural Network

TransNet V2: Shot Boundary Detection Neural Network This repository contains code for TransNet V2: An effective deep network architecture for fast sho

Tomáš Souček 212 Dec 27, 2022
Codebase for Time-series Generative Adversarial Networks (TimeGAN)

Codebase for Time-series Generative Adversarial Networks (TimeGAN)

Jinsung Yoon 532 Dec 31, 2022
Any-to-any voice conversion using synthetic specific-speaker speeches as intermedium features

MediumVC MediumVC is an utterance-level method towards any-to-any VC. Before that, we propose SingleVC to perform A2O tasks(Xi → Ŷi) , Xi means utter

谷下雨 47 Dec 25, 2022
IAUnet: Global Context-Aware Feature Learning for Person Re-Identification

IAUnet This repository contains the code for the paper: IAUnet: Global Context-Aware Feature Learning for Person Re-Identification Ruibing Hou, Bingpe

30 Jul 14, 2022
Pytorch re-implementation of Paper: SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition (CVPR 2022)

SwinTextSpotter This is the pytorch implementation of Paper: SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text R

mxin262 183 Jan 03, 2023
PyTorch implementation of the cross-modality generative model that synthesizes dance from music.

Dancing to Music PyTorch implementation of the cross-modality generative model that synthesizes dance from music. Paper Hsin-Ying Lee, Xiaodong Yang,

NVIDIA Research Projects 485 Dec 26, 2022
KwaiRec: A Fully-observed Dataset for Recommender Systems (Density: Almost 100%)

KuaiRec: A Fully-observed Dataset for Recommender Systems (Density: Almost 100%) KuaiRec is a real-world dataset collected from the recommendation log

Chongming GAO (高崇铭) 70 Dec 28, 2022