feat: add RT factor

README.md

@@ -13,15 +13,18 @@ Pretrained pipelines reach state-of-the-art performance on most academic benchma
 
 | Benchmark             | v1.1 | v2.0 | [v2.1](https://hf.co/pyannote/speaker-diarization-2.1) | [v3.0](https://hf.co/pyannote/speaker-diarization-3.0) |  <a href="mailto:herve-at-niderb-dot-fr?subject=Premium pyannote.audio pipeline&body=Looks like I got your attention! Drop me an email for more details. Hervé.">Premium</a>  |
 | ---------------------- | ---- | ---- | ------ | ------ | --------- |
-| AISHELL-4              | -    | 14.6 |  14.1  |  12.3  | 12.3      |
-| AliMeeting (channel 1) | -    | -    |  27.4  |  24.3  | 19.4      |
-| AMI (IHM)              | 29.7 | 18.2 |  18.9  |  19.0  | 16.7      |
-| AMI (SDM)              | -    | 29.0 |  27.1  |  22.2  | 20.1      |
-| AVA-AVD                | -    | -    |  -     |  49.1  | 42.7      |
-| DIHARD 3 (full)        | 29.2 | 21.0 |  26.9  |  21.7  | 17.0      |
-| MSDWild                | -    | -    |  -     |  24.6  | 20.4      |
-| REPERE (phase2)        | -    | 12.6 |   8.2  |   7.8  |  7.8      |
-| VoxConverse (v0.3)     | 21.5 | 12.6 |  11.2  |  11.3  |  9.5      |
+| AISHELL-4              | -    | 14.6 |  14.1  |  12.3  | 11.9      |
+| AliMeeting (channel 1) | -    | -    |  27.4  |  24.3  | 22.5      |
+| AMI (IHM)              | 29.7 | 18.2 |  18.9  |  19.0  | 16.6      |
+| AMI (SDM)              | -    | 29.0 |  27.1  |  22.2  | 20.9      |
+| AVA-AVD                | -    | -    |  -     |  49.1  | 39.8      |
+| DIHARD 3 (full)        | 29.2 | 21.0 |  26.9  |  21.7  | 17.2      |
+| MSDWild                | -    | -    |  -     |  24.6  | 19.8      |
+| REPERE (phase2)        | -    | 12.6 |   8.2  |   7.8  |  7.6      |
+| VoxConverse (v0.3)     | 21.5 | 12.6 |  11.2  |  11.3  |  9.4      |
 [Diarization error rate](http://pyannote.github.io/pyannote-metrics/reference.html#diarization) (in %)
 
-
+Using one Nvidia Tesla V100 SXM2 GPU and one Intel Cascade Lake 6248 CPU,
+* [v2.1](https://hf.co/pyannote/speaker-diarization-2.1) takes around 1m30s to process 1h of audio
+* [v3.0](https://hf.co/pyannote/speaker-diarization-3.0) takes around 1m20s to process 1h of audio
+* <a href="mailto:herve-at-niderb-dot-fr?subject=Premium pyannote.audio pipeline&body=Looks like I got your attention! Drop me an email for more details. Hervé.">Premium</a> takes around 1m00s to process 1h of audio