| Info hash | 7f06f8280a3b496f2af0f78131ced619df14a0c3 |
| Last mirror activity | 932d,12:14:48 ago |
| Size | 18.45GB (18,448,099,391 bytes) |
| Added | 2022-04-15 14:38:18 |
| Views | 440 |
| Hits | 244 |
| ID | 4785 |
| Type | multi |
| Downloaded | 0 time(s) |
| Uploaded by |  qhliu |
| Folder | MC_GRID |
| Num files | 131934 files [See full list] |
| Mirrors | 0 complete, 1 downloading = 1 mirror(s) total [Log in to see full list] |
MC_GRID (131934 files)
 README.md | 4.04kB |
| grid_vp.pkl | 70.35MB |
| lip_fea/test/s12/bbae1n.npy | 76.93kB |
| lip_fea/test/s12/bbae2s.npy | 76.93kB |
| lip_fea/test/s12/bbae3p.npy | 76.93kB |
| lip_fea/test/s12/bbae4a.npy | 76.93kB |
| lip_fea/test/s12/bbak5n.npy | 76.93kB |
| lip_fea/test/s12/bbak6s.npy | 76.93kB |
| lip_fea/test/s12/bbak7p.npy | 76.93kB |
| lip_fea/test/s12/bbak8a.npy | 76.93kB |
| lip_fea/test/s12/bbaq9n.npy | 76.93kB |
| lip_fea/test/s12/bbar1p.npy | 76.93kB |
| lip_fea/test/s12/bbar2a.npy | 76.93kB |
| lip_fea/test/s12/bbarzs.npy | 76.93kB |
| lip_fea/test/s12/bbay3n.npy | 76.93kB |
| lip_fea/test/s12/bbay4s.npy | 76.93kB |
| lip_fea/test/s12/bbay5p.npy | 76.93kB |
| lip_fea/test/s12/bbay6a.npy | 76.93kB |
| lip_fea/test/s12/bbbe5n.npy | 76.93kB |
| lip_fea/test/s12/bbbe6s.npy | 76.93kB |
| lip_fea/test/s12/bbbe7p.npy | 76.93kB |
| lip_fea/test/s12/bbbe8a.npy | 76.93kB |
| lip_fea/test/s12/bbbk9n.npy | 76.93kB |
| lip_fea/test/s12/bbbl1p.npy | 76.93kB |
| lip_fea/test/s12/bbbl2a.npy | 76.93kB |
| lip_fea/test/s12/bbblzs.npy | 76.93kB |
| lip_fea/test/s12/bbbr3n.npy | 76.93kB |
| lip_fea/test/s12/bbbr4s.npy | 76.93kB |
| lip_fea/test/s12/bbbr5p.npy | 76.93kB |
| lip_fea/test/s12/bbbr6a.npy | 76.93kB |
| lip_fea/test/s12/bbby7n.npy | 76.93kB |
| lip_fea/test/s12/bbby8s.npy | 76.93kB |
| lip_fea/test/s12/bbby9p.npy | 76.93kB |
| lip_fea/test/s12/bbbzza.npy | 76.93kB |
| lip_fea/test/s12/bbid7n.npy | 76.93kB |
| lip_fea/test/s12/bbid8s.npy | 76.93kB |
| lip_fea/test/s12/bbid9p.npy | 76.93kB |
| lip_fea/test/s12/bbieza.npy | 76.93kB |
| lip_fea/test/s12/bbik1n.npy | 76.93kB |
| lip_fea/test/s12/bbik2s.npy | 76.93kB |
| lip_fea/test/s12/bbik3p.npy | 76.93kB |
| lip_fea/test/s12/bbik4a.npy | 76.93kB |
| lip_fea/test/s12/bbiq5n.npy | 76.93kB |
| lip_fea/test/s12/bbiq6s.npy | 76.93kB |
| lip_fea/test/s12/bbiq7p.npy | 76.93kB |
| lip_fea/test/s12/bbiq8a.npy | 76.93kB |
| lip_fea/test/s12/bbix9n.npy | 76.93kB |
| lip_fea/test/s12/bbiy1p.npy | 76.93kB |
| lip_fea/test/s12/bbiy2a.npy | 76.93kB |
Type: Dataset
Tags: Speech Separation, Speaker Extraction
Bibtex:
Tags: Speech Separation, Speaker Extraction
Bibtex:
@article{,
title= {MC_GRID},
journal= {},
author= {Qinghua Liu and Yating Huang and Yunzhe Hao and Jiaming Xu and Bo Xu},
year= {},
url= {},
abstract= {Here we release the dataset (Multi_Channel_Grid, abbreviated as MC_Grid) used in our paper LIMUSE: LIGHTWEIGHT MULTI-MODAL SPEAKER EXTRACTION.
MC_Grid, which is based on GRID dataset, includes multi-channel audio, extracted voiceprint and visual feature. And our code is available at https://github.com/aispeech-lab/LiMuSE.
Feel free to contact us if you have any questions or suggestions.},
keywords= {Speech Separation, Speaker Extraction},
terms= {},
license= {},
superseded= {}
}