update diarization numbers to show on papers with code

README.md

@@ -47,7 +47,7 @@ model-index:
       type: Speaker Diarization
       name: speaker-diarization
     dataset:
-      name: AMI (MixHeadset)
+      name: ami-mixheadset
       type: ami_diarization
       config: oracle-vad-known-number-of-speakers
       split: test
@@ -56,26 +56,12 @@ model-index:
     metrics:
     - name: Test DER
       type: der
-      value: 1.73
+      value: 1.73  
   - task:
       type: Speaker Diarization
       name: speaker-diarization
     dataset:
-      name: AMI (MixHeadset)
-      type: ami_diarization
-      config: oracle-vad-unknown-number-of-speakers
-      split: test
-      args:
-        language: en
-    metrics:
-    - name: Test DER
-      type: der
-      value: 1.89    
-  - task:
-      type: Speaker Diarization
-      name: speaker-diarization
-    dataset:
-      name: AMI (Lapel)
+      name: ami-lapel
       type: ami_diarization
       config: oracle-vad-known-number-of-speakers
       split: test
@@ -89,21 +75,7 @@ model-index:
       type: Speaker Diarization
       name: speaker-diarization
     dataset:
-      name: AMI (Lapel)
-      type: ami_diarization
-      config: oracle-vad-unknown-number-of-speakers
-      split: test
-      args:
-        language: en
-    metrics:
-    - name: Test DER
-      type: der
-      value: 2.03
-  - task:
-      type: Speaker Diarization
-      name: speaker-diarization
-    dataset:
-      name: CH109
+      name: ch109
       type: callhome_diarization
       config: oracle-vad-known-number-of-speakers
       split: test
@@ -117,21 +89,7 @@ model-index:
       type: Speaker Diarization
       name: speaker-diarization
     dataset:
-      name: CH109
-      type: callhome_diarization
-      config: oracle-vad-unknown-number-of-speakers
-      split: test
-      args:
-        language: en
-    metrics:
-    - name: Test DER
-      type: der
-      value: 1.63
-  - task:
-      type: Speaker Diarization
-      name: speaker-diarization
-    dataset:
-      name: NIST SRE 2000
+      name: nist-sre-2000
       type: nist-sre_diarization
       config: oracle-vad-known-number-of-speakers
       split: test
@@ -141,20 +99,6 @@ model-index:
     - name: Test DER
       type: der
       value: 6.73
-  - task:
-      type: Speaker Diarization
-      name: speaker-diarization
-    dataset:
-      name: NIST SRE 2000
-      type: nist-sre_diarization
-      config: oracle-vad-unknown-number-of-speakers
-      split: test
-      args:
-        language: en
-    metrics:
-    - name: Test DER
-      type: der
-      value: 5.38
 ---
 
 # NVIDIA TitaNet-Large (en-US)
@@ -176,7 +120,7 @@ See the [model architecture](#model-architecture) section and [NeMo documentatio
 
 ## NVIDIA NeMo: Training
 
-To train, fine-tune or play with the model you will need to install [NVIDIA NeMo](https://github.com/NVIDIA/NeMo). We recommend you install it after you've installed latest Pytorch version.
+To train, fine-tune or play with the model you will need to install [NVIDIA NeMo](https://github.com/NVIDIA/NeMo). We recommend you install it after you've installed the latest Pytorch version.
 ```
 pip install nemo_toolkit['all']
 ```