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HI-MIA
Audio
NLP
|...
License: Apache-2.0

Overview

The data is used in AISHELL Speaker Verification Challenge 2019. It is extracted from a larger
database called AISHELL-WakeUp-1.
The contents are wake-up words "Hi, Mia" in both Chinese
and English. The data is collected in real home environment using microphone arrays and Hi-Fi
microphone. The collection process and development of a baseline system was described in the
paper below. The data used in the challenge is extracted from 1 Hi-Fi microphone and 16-channel
circular microphone arrays for 1/3/5 meters. And the contents are the Chinese wake-up words.
The whole set is divided into train (254 people), dev (42 people) and test (44 people) subsets.
Test subset is provided with paired target/non-target answer to evaluate verification results.

Citation

Please use the following citation when referencing the dataset:

@misc{himia,
    title={HI-MIA : A Far-field Text-Dependent Speaker Verification Database and the Baselines},
    author={Xiaoyi Qin and Hui Bu and Ming Li},
    year={2019},
    eprint={1912.01231},
    archivePrefix={arXiv},
    primaryClass={cs.SD}
}

License

Apache-2.0

Data Summary
Type
Audio,
Amount
--
Size
43.43GB
Provided by
AISHELL
Aishell is an innovative company focusing on artificial intelligence, big data and technical services.
| Amount -- | Size 43.43GB
HI-MIA
Audio
NLP
License: Apache-2.0

Overview

The data is used in AISHELL Speaker Verification Challenge 2019. It is extracted from a larger
database called AISHELL-WakeUp-1.
The contents are wake-up words "Hi, Mia" in both Chinese
and English. The data is collected in real home environment using microphone arrays and Hi-Fi
microphone. The collection process and development of a baseline system was described in the
paper below. The data used in the challenge is extracted from 1 Hi-Fi microphone and 16-channel
circular microphone arrays for 1/3/5 meters. And the contents are the Chinese wake-up words.
The whole set is divided into train (254 people), dev (42 people) and test (44 people) subsets.
Test subset is provided with paired target/non-target answer to evaluate verification results.

Citation

Please use the following citation when referencing the dataset:

@misc{himia,
    title={HI-MIA : A Far-field Text-Dependent Speaker Verification Database and the Baselines},
    author={Xiaoyi Qin and Hui Bu and Ming Li},
    year={2019},
    eprint={1912.01231},
    archivePrefix={arXiv},
    primaryClass={cs.SD}
}

License

Apache-2.0

0
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