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---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: dev
path: data/dev-*
- split: test
path: data/test-*
dataset_info:
features:
- name: correct_audio
dtype:
audio:
sampling_rate: 16000
- name: correct_transcription
dtype: string
- name: correct_file
dtype: string
- name: wrong_audio
dtype:
audio:
sampling_rate: 16000
- name: wrong_transcription
dtype: string
- name: wrong_file
dtype: string
splits:
- name: train
num_bytes: 25161014072.682
num_examples: 105241
- name: dev
num_bytes: 3494489553.808
num_examples: 14244
- name: test
num_bytes: 3315850038.204
num_examples: 14081
download_size: 31574494786
dataset_size: 31971353664.693996
license: mit
language:
- fr
- en
---
This dataset contains the French-English track of the benchmark from ICASSP 2024: Zero Resource Code-Switched Speech Benchmark Using Speech Utterance Pairs for Multiple Spoken Languages.
Though the benchmark is originally designed to assess the semantic and syntactic abilities of the speech foundation models, you can also use this dataset for code-switching ASR.
If you find this dataset helpful, please consider to cite the following paper:
```
@INPROCEEDINGS{10446737,
author={Huang, Kuan-Po and Yang, Chih-Kai and Fu, Yu-Kuan and Dunbar, Ewan and Lee, Hung-Yi},
booktitle={ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title={Zero Resource Code-Switched Speech Benchmark Using Speech Utterance Pairs for Multiple Spoken Languages},
year={2024},
volume={},
number={},
pages={10006-10010},
keywords={Speech coding;Benchmark testing;Signal processing;Linguistics;Acoustics;Speech processing;Task analysis;Code-switch;Multilingual;Discrete unit;Zero resource;Self-supervised},
doi={10.1109/ICASSP48485.2024.10446737}}
``` |