Datasets:
flac audioduration (s) 1 20 | __key__ stringlengths 48 51 | __url__ stringclasses 1 value |
|---|---|---|
./Scaling_10/MSP-PODCAST_0841/MSP-PODCAST_0841_178 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_0841/MSP-PODCAST_0841_181 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_1246/MSP-PODCAST_1246_12 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_1246/MSP-PODCAST_1246_20 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_1246/MSP-PODCAST_1246_46 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_1246/MSP-PODCAST_1246_58 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_1246/MSP-PODCAST_1246_64 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_1246/MSP-PODCAST_1246_84 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_1246/MSP-PODCAST_1246_91 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_1246/MSP-PODCAST_1246_118 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_1246/MSP-PODCAST_1246_162 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_1246/MSP-PODCAST_1246_190 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_1246/MSP-PODCAST_1246_193 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_0 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_5 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_9 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_14 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_23 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_38 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_54 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_60 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_61 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_64 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_65 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_66 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_68 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_72 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_83 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_85 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_86 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_87 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_89 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_90 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_94 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_95 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_98 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_99 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_103 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_105 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_106 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_107 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_116 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_117 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_119 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_121 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_122 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_124 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_125 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_126 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_130 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_138 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_139 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_144 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_146 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_148 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_152 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_155 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_158 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_159 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_160 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_161 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_162 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_166 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_167 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_168 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_170 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_172 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_183 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_184 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_186 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_187 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_189 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_190 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_192 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_194 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_199 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_200 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_201 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_203 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_208 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_209 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_228 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_230 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_233 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_235 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_236 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_241 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_245 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_246 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_248 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_249 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_253 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_258 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_259 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_260 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_262 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_263 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_264 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_267 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz | |
./Scaling_10/MSP-PODCAST_6583/MSP-PODCAST_6583_289 | hf://datasets/JHU-SmileLab/NaturalVoices_VC_0.1@957eda2a2a87ff407b535adcd17917aec6a43059/NaturalVoices_VC_10%.tar.gz |
NaturalVoices VC 10%
A large voice conversion (VC) dataset curated from spontaneous, in-the-wild podcast speech as part of the NaturalVoices project in collaboration with 🤗MSP Lab at CMU LTI. This release provides the 10% subset uniformly sampled from 870-hour VC dataset and subsets mainly intended for training and evaluating emotion-aware voice conversion systems but not limited to VC tasks.
- 📄 Paper: NaturalVoices: A Large-Scale, Spontaneous and Emotional Podcast Dataset for Voice Conversion — https://arxiv.org/abs/2511.00256 \
- 🧺 Dataset collection (related subsets, e.g., 10% of data & emotional VC): https://huggingface.co/collections/JHU-SmileLab/naturalvoices-voice-conversion-datasets \
-
The extensive (unfiltered) NaturalVoices dataset and the code for the data collection & curation pipeline: https://github.com/Lab-MSP/NaturalVoices
Dataset Summary
NaturalVoices VC compiles real-life, expressive podcast speech and provides automatic annotations designed for VC research (e.g., emotion attributes, speaker identity, speech quality, transcripts). The broader NaturalVoices corpus contains thousands of hours of podcast speech; this repository hosts the VC_01 subset.
What’s in this repo
~90 hours of podcast speech tailored and preprocessed for VC.
A wide range of speakers, both manually & automatically annotated.
Annotations archive with per-utterance annotations including:
- Emotion categorical labels & dimensional attributes (valence/arousal/dominance),
- Speech quality indicators,
- Text, Gender, and Duration.
Subsets
| Subset | Description | Link |
|---|---|---|
| NaturalVoices_VC_870h | 870h of speech data curated for VC | 🤗JHU-SmileLab/NaturalVoices_VC_870h |
| NaturalVoices_EVC | Emotion-balanced subset for Emotional Voice Conversion (EVC) | 🤗JHU-SmileLab/NaturalVoices_EVC |
| NaturalVoices_VC_01 (10%) | A smaller subset uniformly sampled from 870h (10%) | This repo |
How to use
You can directly download the dataset using the following command:
huggingface-cli download JHU-SmileLab/NaturalVoices_VC_0.1 --repo-type=dataset --local-dir=YOUR_LOCAL_DIR
Streaming support will be available
Cite & Contribute
If you use this dataset, please cite the paper:
@misc{du2025naturalvoiceslargescalespontaneousemotional,
title={NaturalVoices: A Large-Scale, Spontaneous and Emotional Podcast Dataset for Voice Conversion},
author={Zongyang Du and Shreeram Suresh Chandra and Ismail Rasim Ulgen and Aurosweta Mahapatra and Ali N. Salman and Carlos Busso and Berrak Sisman},
year={2025},
eprint={2511.00256},
archivePrefix={arXiv},
primaryClass={eess.AS},
url={https://arxiv.org/abs/2511.00256},
}
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