Update README.md

README.md

@@ -2,6 +2,8 @@
 language: ru
 datasets:
 - SberDevices/Golos
+- bond005/sova_rudevices
+- bond005/rulibrispeech
 metrics:
 - wer
 - cer
@@ -12,7 +14,7 @@ tags:
 - xlsr-fine-tuning-week
 license: apache-2.0
 widget:
-- example_title: test sound with Russian speech
+- example_title: test sound with Russian speech "нейросети это хорошо"
   src: https://huggingface.co/bond005/wav2vec2-large-ru-golos/resolve/main/test_sound_ru.flac
 model-index:
 - name: XLSR Wav2Vec2 Russian by Ivan Bondarenko
@@ -27,10 +29,10 @@ model-index:
     metrics:
        - name: Test WER
          type: wer
-         value: 6.271
+         value: 10.144
        - name: Test CER
          type: cer
-         value: 1.292
+         value: 2.168
   - task:
       name: Speech Recognition
       type: automatic-speech-recognition
@@ -41,10 +43,10 @@ model-index:
     metrics:
        - name: Test WER
          type: wer
-         value: 15.653
+         value: 20.353
        - name: Test CER
          type: cer
-         value: 4.349
+         value: 6.030
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
@@ -55,10 +57,10 @@ model-index:
     metrics:
       - name: Test WER
         type: wer
-        value: 23.897
+        value: 18.548
       - name: Test CER
         type: cer
-        value: 4.919
+        value: 4.000
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
@@ -69,10 +71,10 @@ model-index:
     metrics:
       - name: Test WER
         type: wer
-        value: 41.822
+        value: 25.410
       - name: Test CER
         type: cer
-        value: 13.624
+        value: 7.965
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
@@ -83,10 +85,24 @@ model-index:
     metrics:
       - name: Test WER
         type: wer
-        value: 29.664
+        value: 21.872
       - name: Test CER
         type: cer
-        value: 5.747
+        value: 4.469
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Voxforge Ru
+      type: dangrebenkin/voxforge-ru-dataset
+      args: ru
+    metrics:
+      - name: Test WER
+        type: wer
+        value: 27.084
+      - name: Test CER
+        type: cer
+        value: 6.986
 ---
 
 # Wav2Vec2-Large-Ru-Golos
@@ -188,13 +204,13 @@ print("Character error rate on the Farfield domain:", farfield_cer)
 
 | "crowd" | "farfield" |
 |---------|------------|
-|   6.271 |     15.653 |
+|  10.144 |     20.353 |
 
 *Result (CER, %)*:
 
 | "crowd" | "farfield" |
 |---------|------------|
-|   1.292 |      4.349 |
+|   2.168 |      6.030 |
 
 You can see the evaluation script on other datasets, including Russian Librispeech and SOVA RuDevices, on my Kaggle web-page https://www.kaggle.com/code/bond005/wav2vec2-ru-eval