ASVspoof 2019 LA Listening Test Data for Partial Rank Similarity MOS Prediction

This dataset is a derivitave work of the ASVSpoof 2019 LA condition listening test data found here:<br> https://datashare.ed.ac.uk/handle/10283/3336<br> -&gt; LA.zip "ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech" <br> Xin Wang, Junichi Yamagishi, Massimiliano Todisco, Héctor Delgado, Andreas Nautsch, Nicholas Evans, Md Sahidullah, Ville Vestman, Tomi Kinnunen, Kong Aik Lee, Lauri Juvela, Paavo Alku, Yu-Huai Peng, Hsin-Te Hwang, Yu Tsao, Hsin-Min Wang, Sébastien Le Maguer, Markus Becker, Fergus Henderson, Rob Clark, Yu Zhang, Quan Wang, Ye Jia, Kai Onuma, Koji Mushika, Takashi Kaneda, Yuan Jiang, Li-Juan Liu, Yi-Chiao Wu, Wen-Chin Huang, Tomoki Toda, Kou Tanaka, Hirokazu Kameoka, Ingmar Steiner, Driss Matrouf, Jean-François Bonastre, Avashna Govender, Srikanth Ronanki, Jing-Xuan Zhang, Zhen-Hua Ling.<br> Computer Speech and Language Colume 64, 2020. This form of the data was used for the PRS paper accepted to ASRU 2023: "Partial Rank Similarity Minimization Method for Quality MOS Prediction of <br> Unseen Speech Synthesis Systems in Zero-shot and Semi-supervised Setting."<br> Hemant Yadav, Erica Cooper, Junichi Yamagishi, Sunayana Sitaram, Rajiv Ratn Shah. Modifications to the original data include converting audio from flac -&gt; wav, sv56 normalization, conversion of labels from an 0-9 rating scale to a 1-5 scale, and creation of training/development/testing splits.