Update README.md

README.md

@@ -17,7 +17,7 @@ Ke-Omni-R is an advanced audio reasoning model built upon [Qwen2.5-Omni-7B](http
 - **KL Divergence**: Slight improvements were observed during GRPO training by leveraging KL divergence.
 - **Domain Ratio vs. Data Volume**: Domain diversity outweighs data volume. We utilized only 10k samples, with 5k randomly selected from AVQA and another 5k from MusicBench.
 
-## Performance: Accuracies (%) on MMAU Test-mini and Test benchmark
+## Performance: Accuracies (%)↑ on MMAU Test-mini and Test benchmark
 | Model                                 | Method                | Sound (Test-mini) | Sound (Test)  | Music (Test-mini) | Music (Test)  | Speech (Test-mini) | Speech (Test)  | Average (Test-mini) | Average (Test)  |
 |---------------------------------------|-----------------------|-----------|-------|-----------|-------|-----------|------|------------|-------|
 | -                                     | Human\*               | 86.31     | -     | 78.22     | -     | 82.17     | -     | 82.23     | -     |
@@ -34,6 +34,14 @@ Ke-Omni-R is an advanced audio reasoning model built upon [Qwen2.5-Omni-7B](http
 | Qwen2.5-Omni-7B                       | \[4\]                 | 67.87     | -     | 69.16     | -     | 59.76     | -     | 65.60     | -     |
 | Ke-Omni-R(Qwen2.5-Omni-7B)            | GRPO(ours)            | 69.37 | **71.90** | 69.46 | 67.13 |**67.87**  | 67.10 | **68.90** |**68.71** |
 
+## Performance: CER/WER (%)↓ on ASR benchmark
+| Model                 | Method        |  WenetSpeech test-net | WenetSpeech test-meeting | LibriSpeech test-clean | LibriSpeech test-other|
+| ---|----| ----| ----| ---- | ----|
+| Qwen2.5-Omni-3B | \[4\] |  6.3 | 8.1 | 2.2 | 4.5 |
+| Qwen2.5-Omni-7B | \[4\] | 5.9 | 7.7 | 1.8 | 3.4 |
+| Ke-Omni-3B | ours | 11.7 | 16.1 | 1.8 | 3.8 |
+| Ke-Omni-7B | ours | 7.5 | 9.8 | **1.6** | **3.1** |
+
 Note:
 
 - \* The data are sourced from the [MMAU leaderboard](https://sakshi113.github.io/mmau_homepage/#leaderboard).