Removed disclaimer from README
Browse files
README.md
CHANGED
|
@@ -30,16 +30,14 @@ model-index:
|
|
| 30 |
---
|
| 31 |
# Wav2vec 2.0 large VoxRex Swedish (C)
|
| 32 |
|
| 33 |
-
|
|
|
|
|
|
|
| 34 |
|
| 35 |
**Update 2022-01-10:** Updated to VoxRex-C version.
|
| 36 |
|
| 37 |
**Update 2022-05-16:** Paper is is [here](https://arxiv.org/abs/2205.03026).
|
| 38 |
|
| 39 |
-
Finetuned version of KBs [VoxRex large](https://huggingface.co/KBLab/wav2vec2-large-voxrex) model using Swedish radio broadcasts, NST and Common Voice data. Evalutation without a language model gives the following: WER for NST + Common Voice test set (2% of total sentences) is **2.5%**. WER for Common Voice test set is **8.49%** directly and **7.37%** with a 4-gram language model.
|
| 40 |
-
|
| 41 |
-
When using this model, make sure that your speech input is sampled at 16kHz.
|
| 42 |
-
|
| 43 |
# Performance\*
|
| 44 |
|
| 45 |

|
|
|
|
| 30 |
---
|
| 31 |
# Wav2vec 2.0 large VoxRex Swedish (C)
|
| 32 |
|
| 33 |
+
Finetuned version of KBs [VoxRex large](https://huggingface.co/KBLab/wav2vec2-large-voxrex) model using Swedish radio broadcasts, NST and Common Voice data. Evalutation without a language model gives the following: WER for NST + Common Voice test set (2% of total sentences) is **2.5%**. WER for Common Voice test set is **8.49%** directly and **7.37%** with a 4-gram language model.
|
| 34 |
+
|
| 35 |
+
When using this model, make sure that your speech input is sampled at 16kHz.
|
| 36 |
|
| 37 |
**Update 2022-01-10:** Updated to VoxRex-C version.
|
| 38 |
|
| 39 |
**Update 2022-05-16:** Paper is is [here](https://arxiv.org/abs/2205.03026).
|
| 40 |
|
|
|
|
|
|
|
|
|
|
|
|
|
| 41 |
# Performance\*
|
| 42 |
|
| 43 |

|