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| # LSTM Melody Generator | ||
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| This project is aimed at creating a deep learning model using Long Short-Term Memory (LSTM) for generating melodies. The model is trained on a dataset of MIDI files to learn the patterns and relationships in musical sequences. | ||
| This project is aimed at creating a deep learning model using Long Short-Term Memory (LSTM) for generating melodies. The model is trained on a [dataset](https://kern.humdrum.org/), specifically from the Alsace (eastern France) of MIDI files to learn the patterns and relationships in musical sequences. | ||
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| ## Getting Started | ||
| These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. | ||
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| ### Prerequisites | ||
| The following packages are required to run this project: | ||
| 1. [TensorFlow](https://www.tensorflow.org/install) | ||
| 2. [NumPy](https://numpy.org/) | ||
| 3. [Music21](http://web.mit.edu/music21/) | ||
| ## Dataset | ||
| The dataset used on this project is from (Alsace)[https://kern.humdrum.org/cgi-bin/ksdata?l=essen/europa/elsass&format=zip], a historical region in France where they have plenty of collected compositions in `.krn` files that can be accessed using any music notation softwares. | ||
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| ### Installation | ||
| 1. Clone the repository to your local machine | ||
| ## Installation | ||
| The following packages required to access and manipulate musical notations: | ||
| 1. [Musecore](https://musescore.org/en) | ||
| 2. [Music21](http://web.mit.edu/music21/) | ||
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| ### Installation | ||
| Start by cloning the repository to your local machine | ||
| `git clone https://github.com/<username>/rnn-lstm-melody-generator.git` | ||
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| 2. Navigate to the project directory | ||
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| `cd rnn-lstm-melody-generator` | ||
| Set the MuseScore3 path to view the notations of `.krn` file sets | ||
| ``` | ||
| # set the default musicxmlPath file reader to MuseScore3.exe | ||
| us = m21.environment.UserSettings() | ||
| us["musicxmlPath"] = 'C:/Program Files/MuseScore 3/bin/MuseScore3.exe' | ||
| ``` | ||
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| ### Usage | ||
| To preprocess the model, run the following command | ||
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| 1. Towards the preprocessing, provided are `.txt` files from the `.krn` file sets and are then tokenized stored within `mapping.json` as `file_dataset` being the final output of preprocessing | ||
| `python preprocess.py` | ||
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| To train the model, run the following command | ||
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| 2. For training, an `.h5` file is produced for creating the melody | ||
| `python train.py` | ||
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| To generate the model, run the following command | ||
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| To generate the model, run the following command; the seeds can be configured to the formatting required. | ||
| `python melody_generator.py` | ||
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| ### Acknowledgments | ||
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| [Valerio Velardo - The Sound of AI](https://www.youtube.com/@ValerioVelardoTheSoundofAI) | ||
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