add section Available models and languages

README.md

@@ -35,9 +35,30 @@ choco install ffmpeg
 ```
 
 
+## Available models and languages
+
+There are five model sizes, four with English-only versions, offering speed and accuracy tradeoffs. Below are the names of the available models and their approximate memory requirements and relative speed. 
+
+
+|  Size  | Parameters | English-only model | Multilingual model | Required VRAM | Relative speed |
+|:------:|:----------:|:------------------:|:------------------:|:-------------:|:--------------:|
+|  tiny  |    39 M    |     `tiny.en`      |       `tiny`       |     ~1 GB     |      ~32x      |
+|  base  |    74 M    |     `base.en`      |       `base`       |     ~1 GB     |      ~16x      |
+| small  |   244 M    |     `small.en`     |      `small`       |     ~2 GB     |      ~6x       |
+| medium |   769 M    |    `medium.en`     |      `medium`      |     ~5 GB     |      ~2x       |
+| large  |   1550 M   |        N/A         |      `large`       |    ~10 GB     |       1x       |
+
+For English-only applications, the `.en` models tend to perform better, especially for the `tiny.en` and `base.en` models. We observed that the difference becomes less significant for the `small.en` and `medium.en` models.
+
+Whisper's performance varies widely depending on the language. The figure below shows a WER breakdown by languages of Fleurs dataset, using the `large` model. More WER and BLEU scores corresponding to the other models and datasets can be found in Appendix D in [the paper](https://cdn.openai.com/papers/whisper.pdf).
+
+![WER breakdown by language](language-breakdown.svg)
+
+
+
 ## Command-line usage
 
-There are five model sizes, four with English-only versions, offering speed and accuracy tradeoffs. The following command will transcribe speech in audio files, using the `medium` model:
+The following command will transcribe speech in audio files, using the `medium` model:
 
     whisper audio.flac audio.mp3 audio.wav --model medium