final proofread

docs/lmms-eval-0.3.md

@@ -112,7 +112,7 @@ This upgrade includes multiple benchmarks for audio understanding and instructio
 | **AIRBench** | 2024 | air_bench_chat \| air_bench_foundation | chat, foundation | AIF | GPT-4 Eval (chat) \| Accuracy (foundation) | 2k (chat) \| 19k (foundation) | 1. Comprhensive tasks and audio types |
 | **Alpaca Audio** | 2024 | alpaca_audio | test | AIF | GPT-4 Eval | 100 | 1. Synthetic voice |
 | **Clotho-AQA** | 2022 | clotho_aqa | test \| val | AIF | Accuracy | test_v2 (2.06k), test \| val (1.44k \| 1.05k) | 1. Audio Question Answering<br> 2. Single word answer<br> 3. Text based question |
-| **Common_voice** | 2023 | common_voice_15 | test | ASR | WER(↓)(align with Qwen-audio) | en (16.4k) \| fr (16.1k) \| zh (10.6k) | 1. Real people voice<br> 2. Captioning |
+| **Common_voice** | 2023 | common_voice_15 | test | ASR | WER(↓) (align with Qwen-audio) | en (16.4k) \| fr (16.1k) \| zh (10.6k) | 1. Real people voice<br> 2. Captioning |
 | **GigaSpeech** | 2021 | gigaspeech | test \| dev | ASR | WER(↓)| dev (6.75k) \| test (25.6k) | 1. Transciption<br> 2. Audio book<br> 3. YouTube<br> 4. Podcasts |
 | **LibriSpeech** | 2015 | librispeech | dev-clean \| dev-other \| test-clean \| test-other | ASR | WER(↓)| dev-clean (~2.48k) \|<br>dev-other (~2.66k) \|<br>test-clean(~2.55k) \|<br> test-other (~2.70k) | 1. Transcription (audio book) |
 | **OpenHermes** | 2024 | openhermes | test | AIF | GPT-Eval | 100 | 1. Synthetic voice |