SUSHI🍣: A Dataset of Synthetic Unichannel Signals Based on Heuristic Implementation (Tiny)

Overview

This dataset consists of pairs of time series signal data and corresponding natural language texts that describe the characteristics of these time series patterns. It has been designed with the objective of creating and evaluating a foundational model that facilitates natural language processing tasks, such as query-by-text retrieval for time series signals and captioning for these signals. All time series signals included in this dataset have been artificially generated from predefined combinations of multiple classes of functions. In addition, the paired natural language texts are primarily based on texts randomly selected from a pre-registered list corresponding to the functions, which have been manually refined through visual inspection.

Specification

We have two versions. This page provides "Tiny" under the Creative Commons Attribution 4.0 International license.

Spec
Tiny
Base

Samples
1.4K
140K

Time length
2048 points
2048 points

Format
CSV, NPY, PNG
CSV, NPY, PNG

In addition, when “SUSHI” is referred to without the word “Tiny” in a paper or other document, it shall be taken to mean “Base”.

Detailed Information

The detailed infromation is availtable in the following documents:

Arxiv preprint: Yohei Kawaguchi, Kota Dohi, and Aoi Ito, "SUSHI: A Dataset of Synthetic Unichannel Signals Based on Heuristic Implementation," in arXiv e-prints: zzzzzzz, 2024. http://,,,,

Githut repository: https://github.com/y-kawagu/SUSHI/ 

Citation

If you use this dataset, please cite the following paper:

Yohei Kawaguchi, Kota Dohi, and Aoi Ito, "SUSHI: A Dataset of Synthetic Unichannel Signals Based on Heuristic Implementation," in arXiv e-prints: zzzzzzz, 2024. [URL]