SIMS
Collection
Models and evaluation data from the paper: "Scaling Analysis of Interleaved Speech-Text Language Models"
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A multispeaker spoken version of StoryCloze Synthesized with Kokoro TTS. The dataset was synthesized to evaluate the performance of speech language models as detailed in the paper "Scaling Analysis of Interleaved Speech-Text Language Models".
We refer you to the SlamKit codebase to see how you can evaluate your SpeechLM with this dataset.
We split the generation for spoken-stroycloze and topic-storycloze as detailed in Twist.
from datasets import load_dataset
dataset = load_dataset("slprl/multispeaker-storycloze")
The data has several fields:
id
: the file id as in the original StoryCloze dataset.correct_text
: the text of the correct sample.correct_audio
: the synthesized audio of the correct sample.incorrect_text
: the text of the incorrect sample.incorrect_audio
: the synthesized audio of the incorrect sample.If you use this version of the dataset please cite our work:
@misc{maimon2025scaling,
title={Scaling Analysis of Interleaved Speech-Text Language Models},
author={Gallil Maimon and Michael Hassid and Amit Roth and Yossi Adi},
year={2025},
eprint={2504.02398},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2504.02398},
}