Datasets:
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,12 +1,12 @@
|
|
| 1 |
-
---
|
| 2 |
-
task_categories:
|
| 3 |
-
- audio-to-audio
|
| 4 |
-
tags:
|
| 5 |
-
- music
|
| 6 |
-
pretty_name: YouTubeBigBand
|
| 7 |
-
size_categories:
|
| 8 |
-
- n<1K
|
| 9 |
-
---
|
| 10 |
# YouTubeBigBand Dataset
|
| 11 |
|
| 12 |
Inspired by the [YouTubeMix](https://huggingface.co/datasets/krandiash/youtubemix) dataset.
|
|
@@ -15,7 +15,7 @@ Inspired by the [YouTubeMix](https://huggingface.co/datasets/krandiash/youtubemi
|
|
| 15 |
*Source*: [https://www.youtube.com/watch?v=I4KAKqF4mjE](https://www.youtube.com/watch?v=I4KAKqF4mjE) - a 2 hour long mix of jazz tracks played by a big band.
|
| 16 |
<br/>
|
| 17 |
<br/>
|
| 18 |
-
Used for pre-training a [SaShiMi model (see citation)](https://arxiv.org/abs/2202.09729) as part of Tel Aviv University Deep Learning Workshop 2024 Semester B.
|
| 19 |
|
| 20 |
We include two versions of the dataset:
|
| 21 |
- `youtubebigband.zip` is a zip file containing 129 1-minute audio clips (re)sampled at 16kHz. These were generated by splitting the original audio track.
|
|
|
|
| 1 |
+
---
|
| 2 |
+
task_categories:
|
| 3 |
+
- audio-to-audio
|
| 4 |
+
tags:
|
| 5 |
+
- music
|
| 6 |
+
pretty_name: YouTubeBigBand
|
| 7 |
+
size_categories:
|
| 8 |
+
- n<1K
|
| 9 |
+
---
|
| 10 |
# YouTubeBigBand Dataset
|
| 11 |
|
| 12 |
Inspired by the [YouTubeMix](https://huggingface.co/datasets/krandiash/youtubemix) dataset.
|
|
|
|
| 15 |
*Source*: [https://www.youtube.com/watch?v=I4KAKqF4mjE](https://www.youtube.com/watch?v=I4KAKqF4mjE) - a 2 hour long mix of jazz tracks played by a big band.
|
| 16 |
<br/>
|
| 17 |
<br/>
|
| 18 |
+
Used for pre-training a [SaShiMi model (see citation)](https://arxiv.org/abs/2202.09729) as part of Tel Aviv University Deep Learning Workshop 2024 Semester B (see [project repository fork](https://github.com/galbezalel/s4-dl-workshop/)).
|
| 19 |
|
| 20 |
We include two versions of the dataset:
|
| 21 |
- `youtubebigband.zip` is a zip file containing 129 1-minute audio clips (re)sampled at 16kHz. These were generated by splitting the original audio track.
|