TapToTab: A Pitch-Labelled Guitar Dataset for Note Recognition

Citation Author(s):
Eslam
ElSadawy
Ain Shams University
Ihab
Essam
Ain Shams University
Ali
Ghaleb
Ain Shams University
Mohamed
Abdelhakim
Ain Shams University
Seif-Eldin
Zaki
Ain Shams University
Natalie
Fahim
Ain Shams University
Razan
Bayoumi
Ain Shams University
Hanan
Hindy
Ain Shams University
Submitted by:
Hanan Hindy
Last updated:
Wed, 09/04/2024 - 17:11
DOI:
10.21227/664p-5b45
Data Format:
License:
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Abstract 

The limited availability of Guitar notes datasets hinders the training of any artificial intelligence model in this field. TaptoTab dataset aims to fill this gap by providing a collection of notes recordings. This dataset is collected as part of an honours project at the Faculty of Computer and Information Sciences, Ain Shams University. The dataset is composed of audio data that has been self-collected, focusing on capturing a comprehensive range of guitar notes. The dataset consists of recordings of guitar notes played on each of the six strings, covering up to the 12th fret. This ensures that a wide spectrum of notes is represented, catering to the most commonly used range in guitar playing. Furthermore, the dataset has a variation of clean and distorted note recordings with effects added to both.

Instructions: 

The dataset is composed of:

  • 78: clean notes.
  • 78: distorted notes.
  • 156: note effects.

Each audio file in the dataset is named using the format "A#2-Bb2-0_01.478", where the name begins with the note played (e.g., A#2 or Bb2) and is followed by the exact onset time (in seconds) at which the note was played. Each recording features a single note played for varying durations, providing diverse data points for any AI to learn from.

 

Comments

Goog dataset. Exactly what I was looking for. Thanks

Submitted by Francky SAAH on Mon, 09/30/2024 - 12:06

Documentation

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File TapToTabV2.pdf72.28 KB