Create README.md

README.md

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+---
+license: apache-2.0
+---
+
+
+---
+
+Data source:
+https://openslr.org/93/
+
+Audios and transcriptions are extracted to wav and txt files.
+
+---
+
+
+
+
+
+<div class="container">
+<h2 class="slrStyle"> AISHELL-4
+ </h2>
+<p class="resource"> <b>Identifier:</b> SLR111 </p>
+<p class="resource"> <b>Summary:</b> A Free Mandarin Multi-channel Meeting Speech Corpus, provided by Beijing Shell Shell Technology Co.,Ltd
+ </p>
+<p class="resource"> <b>Category:</b> Speech
+ </p>
+<p class="resource"> <b>License:</b> CC BY-SA 4.0
+ </p>
+<p class="resource"> <b>Downloads (use a mirror closer to you):</b> <br>
+<a href="https://www.openslr.org/resources/111/train_L.tar.gz"> train_L.tar.gz </a> [7.0G] &nbsp; ( Training set of large room, 8-channel microphone array speech
+) &nbsp;  Mirrors: 
+<a href="https://us.openslr.org/resources/111/train_L.tar.gz"> [US] </a> &nbsp;
+<a href="https://openslr.elda.org/resources/111/train_L.tar.gz"> [EU] </a> &nbsp;
+<a href="https://openslr.magicdatatech.com/resources/111/train_L.tar.gz"> [CN] </a> &nbsp;
+<br><a href="https://www.openslr.org/resources/111/train_M.tar.gz"> train_M.tar.gz </a> [25G] &nbsp; ( Training set of medium room, 8-channel microphone array speech
+) &nbsp;  Mirrors: 
+<a href="https://us.openslr.org/resources/111/train_M.tar.gz"> [US] </a> &nbsp;
+<a href="https://openslr.elda.org/resources/111/train_M.tar.gz"> [EU] </a> &nbsp;
+<a href="https://openslr.magicdatatech.com/resources/111/train_M.tar.gz"> [CN] </a> &nbsp;
+<br><a href="https://www.openslr.org/resources/111/train_S.tar.gz"> train_S.tar.gz </a> [14G] &nbsp; ( Training set of small room, 8-channel microphone array speech
+) &nbsp;  Mirrors: 
+<a href="https://us.openslr.org/resources/111/train_S.tar.gz"> [US] </a> &nbsp;
+<a href="https://openslr.elda.org/resources/111/train_S.tar.gz"> [EU] </a> &nbsp;
+<a href="https://openslr.magicdatatech.com/resources/111/train_S.tar.gz"> [CN] </a> &nbsp;
+<br><a href="https://www.openslr.org/resources/111/test.tar.gz"> test.tar.gz </a> [5.2G] &nbsp; (  Test set
+) &nbsp;  Mirrors: 
+<a href="https://us.openslr.org/resources/111/test.tar.gz"> [US] </a> &nbsp;
+<a href="https://openslr.elda.org/resources/111/test.tar.gz"> [EU] </a> &nbsp;
+<a href="https://openslr.magicdatatech.com/resources/111/test.tar.gz"> [CN] </a> &nbsp;
+<br><br></p><p class="resource"><b>About this resource:</b></p><div id="about">The AISHELL-4 is a sizable real-recorded Mandarin speech dataset
+collected by 8-channel circular microphone array for speech processing
+in conference scenarios. The dataset consists of 211 recorded meeting
+sessions, each containing 4 to 8 speakers, with a total length of 120
+hours. This dataset aims to bridge the advanced research on
+multi-speaker processing and the practical application scenario in
+three aspects. With real recorded meetings, AISHELL-4 provides
+realistic acoustics and rich natural speech characteristics in
+conversation such as short pause, speech overlap, quick speaker turn,
+noise, etc. Meanwhile, the accurate transcription and speaker voice
+activity are provided for each meeting in AISHELL-4. This allows the
+researchers to explore different aspects in meeting processing,
+ranging from individual tasks such as speech front-end processing,
+speech recognition and speaker diarization, to multi-modality modeling
+and joint optimization of relevant tasks. We also release a
+PyTorch-based training and evaluation framework as a baseline system to
+promote reproducible research in this field. The baseline system code
+and generated samples are available
+<a href="https://github.com/felixfuyihui/AISHELL-4">here</a>.
+<p>
+
+You can cite the data
+using the following BibTeX entry:
+</p><pre>
+@inproceedings{AISHELL-4_2021,
+title={AISHELL-4: An Open Source Dataset for Speech Enhancement, Separation, Recognition and Speaker Diarization in Conference Scenario},
+author={Yihui Fu, Luyao Cheng, Shubo Lv, Yukai Jv, Yuxiang Kong, Zhuo Chen, Yanxin Hu, Lei Xie, Jian Wu, Hui Bu, Xin Xu, Jun Du, Jingdong Chen},
+booktitle={Interspeech},
+url={https://arxiv.org/abs/2104.03603},
+year={2021}
+}
+</pre>
+</div><p class="resource"> <b>External URL:</b> <a href="http://www.aishelltech.com/aishell_4"> http://www.aishelltech.com/aishell_4 </a> &nbsp;  Full description from the company website
+ </p> 
+
+<div style="height:300px"> </div>
+
+</div>