Contexual-Biasing-Dataset

paper: CB-Conformer: Contextual biasing Conformer for biased word recognition

This repository contains the Mandarin biased words dataset with five sub-datasets, namely the person-name dataset, the place-name dataset, the organization-name dataset, and the full set of biased words containing all categories called "all_biased" dataset as well as the dataset without biased words called "no_biased" dataset.

Each sub-dataset is divided into train, test, and dev sets, and contains a collection of biased words. The specific dataset sizes are as follows:

	train	dev	test	time(h)	number of biased words
person-name	1000	1000	9997	10.24	73
place-name	1000	1000	10191	12.96	42
organization	1000	500	2035	3.94	183
all_biased	2992	2497	21972	26.77	298
no_biased	12774458	/	/	793.30	/

This dataset is filtered and divided from the WenetSpeech dataset, if you need to use this dataset, you need to do the following steps

1. download the

   [WenetSpeech]: https://wenet.org.cn/WenetSpeech/ ""WenetSpeech""

   dataset

2. Save the wav.scp from WenetSpeech/WenetSpeech/train_m or your own wav.scp to each sub-dataset

3. Call fix_data_dir.sh of the

   [Kaldi]: https://github.com/kaldi-asr/kaldi ""Kaldi""

   tool to process each sub-dataset and you will get a filtered and constructed dataset

citation:

@inproceedings{CB-Conformer,
  title={CB-Conformer: Contextual biasing Conformer for biased word recognition},
  author={Xu, Yaoxun and Liu, Baiji and Huang, Qiaochu and Song, Xingchen and Wu, Zhiyong and Kang, Shiyin and Meng, Helen},
  booktitle={ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={1--5},
  year={2023},
  organization={IEEE}
}