Update README.md

README.md

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   <b>ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis</b>
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+<p align="center"> Hawau Olamide Toyin, Rufael Marew, Humaid Alblooshi, Samar M. Magdy, Hanan Aldarmaki </p>
+<p align="center"> {hawau.toyin, hanan.aldarmaki}@mbzuai.ac.ae </p>
 
 <div style="font-size: 16px; text-align: justify;">
     <p>ArVoice is a multi-speaker Modern Standard Arabic (MSA) speech corpus with fully diacritized transcriptions, intended  for multi-speaker speech synthesis, and can be useful for other tasks such as speech-based diacritic restoration, voice conversion, and deepfake detection. <br> 
       ArVoice comprises: (1) professionally recorded audio by 2 male and 2 female voice artists from diacritized transcripts, (2) professionally recorded audio by 1 male and 1 female voice artists from undiacritized transcripts, (3) a modified subset of the
 Arabic Speech Corpus, and (4) synthesized speech using commercial TTS systems. The complete corpus consists of a total of 83.52 hours of speech across 11 voices; around 10 hours consist of human voices from 7 speakers. <br> <br>
-      <strong> This repo consists of only Parts (3), ASC subset, and (4) synthetic subset </strong>; to access the main subset, part (1,2), which consists of six professional speakers, <a href="/"> please sign this agreement</a> and email it to us. 
+      <strong> This repo consists of only Parts (3), ASC subset, and (4) synthetic subset </strong>; to access the main subset, part (1,2), which consists of six professional speakers, <a href="https://huggingface.co/datasets/MBZUAI/ArVoice/resolve/main/ArVoice%20DUA.pdf"> please sign this agreement</a> and email it to us. 
       <br><br> If you use the dataset or transcriptions provided in Huggingface, <u>place cite the paper</u>. 
 </p>
 </div>
 
+
 Usage Example
 
 ```python