--- license: apache-2.0 language: - zh tags: - speaker-verification - text-dependent-speaker-verification - far-field-speech - wake-up-word - microphone-array - aishell pretty_name: HI-MIA --- # HI-MIA ## Dataset Description HI-MIA is a far-field text-dependent speaker verification database used in the **AISHELL Speaker Verification Challenge 2019**. The data is extracted from a larger database called **AISHELL-WakeUp-1**. The original resource contains wake-up words **"Hi, Mia"** in both Chinese and English. The challenge data provided in this resource uses the Chinese wake-up words. The recordings were collected in real home environments using microphone arrays and a Hi-Fi microphone. The challenge data is extracted from: - 1 Hi-Fi microphone - 16-channel circular microphone arrays - Recording distances of 1 meter, 3 meters, and 5 meters ## Dataset Source The dataset is available from OpenSLR: - OpenSLR: http://openslr.org/85/ - External URL: http://aishelltech.com/wakeup_data ## Dataset Structure The dataset is divided into three subsets: | Split | Number of Speakers | Description | |---|---:|---| | Train | 254 | Training set with speaker-dependent subfolders | | Dev | 42 | Development set with speaker-dependent subfolders | | Test | 44 | Test set with paired target/non-target answer for speaker verification evaluation | OpenSLR provides the following downloadable files: | File | Size | Description | |---|---:|---| | `train.tar.gz` | 36 GB | Training set with speaker-dependent subfolders | | `dev.tar.gz` | 5.1 GB | Development set with speaker-dependent subfolders | | `test.tar.gz` | 4.7 GB | Test set with target/non-target answer | | `test_v2.tar.gz` | 4.7 GB | Updated test set fixing corrupted audio files | | `filename_mapping.tar.gz` | 5.9 MB | Filename mapping rules for multi-channel information | ## Dataset Creation The data was collected in real home environments. The collection process and the development of baseline systems are described in the paper cited below. ## Intended Uses This dataset is intended for research on: - Far-field speaker verification - Text-dependent speaker verification - Wake-up word speaker verification - Microphone-array based speaker verification ## License The dataset is released under the **Apache License v2.0**. ## Citation If you use this dataset, please cite: ```bibtex @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} }