<commit_before># Folk music style modelling using LSTMs

This code was used for the following published works:

1. Sturm, Santos and Korshunova, ["Folk Music Style Modelling by Recurrent Neural Networks with Long Short Term Memory Units"](http://ismir2015.uma.es/LBD/LBD13.pdf), Late-breaking demo at the 2015 Int. Symposium on Music Information Retrieval

2. Sturm, Santos, Ben-Tal and Korshunova, "Music transcription modelling and composition using deep learning", in Proc. [1st Conf. Computer Simulation of Musical Creativity](https://csmc2016.wordpress.com), Huddersfield, UK, July 2016.
<commit_msg>data readme?<commit_after># Folk music style modelling using LSTMs

This is the data we have used.

1. sessions_data_clean.txt: This comes from the [weekly repository of thesession.org](https://github.com/adactio/TheSession-data), except we have cleaned it to a very thorough degree (removing html, comments, etc.).

2. allabcwrepeats_parsed: This is the above but cleaned, and tokenised.

3. allabcworepeats_parsed: This is the above but with the repeats made explicit (converting to midi and back to abc)

{'fraction_non_alphanumeric': 0.07553956834532374, 'fraction_numerical': 0.02158273381294964, 'mean_word_length': 5.081967213114754, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 2, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '7269238', 'n_tokens_mistral': 350, 'n_tokens_neox': 319, 'n_words': 141}