Datasets:
File size: 1,515 Bytes
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---
dataset_info:
features:
- name: id
dtype: string
- name: correct_text
dtype: string
- name: correct_audio
dtype: audio
- name: negative_text
dtype: string
- name: negative_audio
dtype: audio
splits:
- name: train
num_bytes: 2656749331.832
num_examples: 1871
download_size: 2437424339
dataset_size: 2656749331.832
configs:
- config_name: default
data_files:
- split: train
path: sSC/bm/train-*
---
# Multi Speaker StoryCloze
A multispeaker spoken version of [StoryCloze]() Synthesized with [Kokoro TTS](https://huggingface.co/hexgrad/Kokoro-82M).
The dataset was synthesized to evaluate the performance of speech language models as detailed in the paper ["SIMS: Scaling Analysis of Interleaved Speech-Text Language Models"]().
We refer you to the _SlamKit_ [codebase](https://github.com/slp-rl/slamkit) to see how you can evaluate your SpeechLM with this dataset.
## sSC and tSC
Explain about the parts.
## Usage
```python
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:
```
add
```
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