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The info cannot be fetched for the config 'default' of the dataset.
Error code:   InfoError
Exception:    FileNotFoundError
Message:      Couldn't find any data file at /src/services/worker/slprl/multispeaker-storycloze. Couldn't find 'slprl/multispeaker-storycloze' on the Hugging Face Hub either: LocalEntryNotFoundError: An error happened while trying to locate the file on the Hub and we cannot find the requested files in the local cache. Please check your connection and try again or make sure your Internet connection is on.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 211, in compute_first_rows_from_streaming_response
                  info = get_dataset_config_info(path=dataset, config_name=config, token=hf_token)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 278, in get_dataset_config_info
                  builder = load_dataset_builder(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1781, in load_dataset_builder
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1659, in dataset_module_factory
                  raise FileNotFoundError(
              FileNotFoundError: Couldn't find any data file at /src/services/worker/slprl/multispeaker-storycloze. Couldn't find 'slprl/multispeaker-storycloze' on the Hugging Face Hub either: LocalEntryNotFoundError: An error happened while trying to locate the file on the Hub and we cannot find the requested files in the local cache. Please check your connection and try again or make sure your Internet connection is on.

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Multi Speaker StoryCloze

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.

sSC and tSC

We split the generation for spoken-stroycloze and topic-storycloze as detailed in Twist.

Usage

from datasets import load_dataset
dataset = load_dataset("slprl/multispeaker-storycloze")

Data Fields

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.

Citation

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}, 
}
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