Bambara ASR Leaderboard
Where Are We at with Automatic Speech Recognition for the Bambara Language ?
๐ Current Best Model: MALIBA-AI/bambara-asr-v3
- WER: 45.73%
- CER: 13.45%
- Combined Score: 36.05%
- License: Open Source
Main Leaderboard
๐ Custom Ranking Weights
Adjust the sliders below to rank models based on your preference. For example, set WER to 100% and CER to 0% if you only care about Word Error Rate.
Adjust the sliders below to rank models based on your preference. For example, set WER to 100% and CER to 0% if you only care about Word Error Rate.
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Current ranking: 50% WER + 50% CER
| Rank | Model Name | WER (%) | CER (%) | Combined Score (%) | License | Timestamp |
|---|---|---|---|---|---|---|
| 1 | ๐ MALIBA-AI/bambara-asr-v3 | 45.73 | 13.45 | 29.59 | Open Source | 2025-12-23 13:59:12 |
| 2 | ๐ฅ djelia/asr-v2 | 47.50 | 13.56 | 30.53 | Proprietary | 2025-12-13 21:20:03 |
| 3 | ๐ฅ djelia/asr-v1 | 48.56 | 13.00 | 30.78 | Proprietary | 2025-12-13 21:19:09 |
| 4 | RobotsMali/soloba-ctc-0.6b-v3 | 46.76 | 16.02 | 31.39 | Open Source | 2025-12-15 11:56:46 |
| 5 | RobotsMali/soloni-114m-tdt-ctc-v3-ctc-dec | 48.32 | 14.81 | 31.57 | Open Source | 2025-12-15 11:50:57 |
| 6 | RobotsMali/soloni-114m-tdt-ctc-v3 | 48.32 | 14.81 | 31.57 | Open Source | 2025-12-13 22:47:24 |
| 7 | RobotsMali/soloni-114m-tdt-ctc-v2 | 49.42 | 15.58 | 32.50 | Open Source | 2025-12-13 22:49:43 |
| 8 | RobotsMali/soloba-ctc-0.6b-v2 | 48.06 | 17.19 | 32.63 | Open Source | 2025-12-15 11:56:10 |
| 9 | RobotsMali/soloba-ctc-0.6b-v0.5 | 49.93 | 15.33 | 32.63 | Open Source | 2025-12-15 11:57:18 |
| 10 | RobotsMali/soloba-ctc-0.6b-v1.5 | 52.56 | 19.93 | 36.24 | Open Source | 2025-12-15 11:57:50 |
| 11 | facebook/mms-1b-all | 61.06 | 14.71 | 37.88 | Open Source | 2025-12-13 21:21:07 |
| 12 | meta/omniASR_LLM_7B | 62.57 | 15.08 | 38.83 | Open Source | 2025-12-17 19:04:59 |
| 13 | sudoping01/bambara-asr-v2 | 60.33 | 17.46 | 38.90 | Open Source | 2025-12-13 22:17:21 |
| 14 | RobotsMali/soloba-ctc-0.6b-v1 | 57.59 | 20.81 | 39.20 | Open Source | 2025-12-15 11:55:46 |
| 15 | RobotsMali/soloni-114m-tdt-ctc-v0 | 55.79 | 22.65 | 39.22 | Open Source | 2025-12-13 22:54:22 |
| 16 | MALIBA-AI/bambara-asr-v1 | 61.74 | 17.90 | 39.82 | Open Source | 2025-12-13 22:22:44 |
| 17 | MALIBA-AI/bambara-asr-v2 | 61.74 | 17.90 | 39.82 | Open Source | 2025-12-14 03:25:54 |
| 18 | meta/omniASR_LLM_300M | 63.32 | 17.32 | 40.32 | Open Source | 2025-12-17 19:07:11 |
| 19 | Panga-Azazia/bambara-asr-v1.1-0 | 60.39 | 22.60 | 41.49 | Proprietary | 2025-12-15 12:04:02 |
| 20 | RobotsMali/stt-bm-quartznet15x5-v2 | 65.66 | 18.98 | 42.32 | Open Source | 2025-12-13 22:43:12 |
| 21 | djelia/bm-whisper-large-v2-lora-merged | 59.17 | 25.85 | 42.51 | Proprietary | 2025-12-19 19:00:03 |
| 22 | RobotsMali/soloni-114m-tdt-ctc-v1 | 61.14 | 27.69 | 44.41 | Open Source | 2025-12-13 22:50:28 |
| 23 | Panga-Azazia/bambara-asr-ngram | 69.13 | 19.80 | 44.47 | Open Source | 2025-12-15 12:02:28 |
| 24 | Panga-Azazia/bambara-asr | 70.00 | 20.39 | 45.19 | Open Source | 2025-12-13 22:15:17 |
| 25 | meta/omniASR_CTC_1B_v2 | 69.62 | 21.93 | 45.77 | Open Source | 2025-12-17 19:00:16 |
| 26 | RobotsMali/soloba-ctc-0.6b-v0 | 62.93 | 30.48 | 46.70 | Open Source | 2025-12-15 11:54:55 |
| 27 | meta/omniASR_CTC_3B | 72.62 | 21.80 | 47.21 | Open Source | 2025-12-17 19:02:53 |
| 28 | RobotsMali/stt-bm-quartznet15x5-v1 | 72.98 | 21.75 | 47.37 | Open Source | 2025-12-13 22:44:00 |
| 29 | meta/omniASR_LLM_1B | 78.31 | 21.29 | 49.80 | Open Source | 2025-12-17 19:04:21 |
| 30 | meta/omniASR_LLM_CTC_300M | 76.87 | 22.87 | 49.87 | Open Source | 2025-12-17 19:07:54 |
| 31 | meta/omniASR_CTC_7B | 74.65 | 25.47 | 50.06 | Open Source | 2025-12-17 19:03:31 |
| 32 | RobotsMali/stt-bm-quartznet15x5-v0 | 75.82 | 25.23 | 50.53 | Open Source | 2025-12-13 22:44:55 |
| 33 | nvidia/parakeet-tdt-0.6b-v3 | 100.06 | 49.24 | 74.65 | Open Source | 2025-12-17 18:55:17 |
| 34 | sudoping01/maliba-asr-v0 | 94.86 | 71.72 | 83.29 | Open Source | 2025-12-14 03:43:28 |
| 35 | openai/whisper-large-v2 | 106.84 | 60.80 | 83.82 | Open Source | 2025-12-13 21:51:48 |
| 36 | nvidia/canary-1b-v2 | 111.64 | 60.55 | 86.09 | Open Source | 2025-12-17 18:53:59 |
| 37 | openai/whisper-tiny | 112.72 | 66.61 | 89.67 | Open Source | 2025-12-14 13:25:23 |
| 38 | openai/whisper-small | 109.97 | 75.84 | 92.91 | Open Source | 2025-12-14 13:26:31 |
| 39 | openai/whisper-large-v3 | 121.06 | 75.10 | 98.08 | Open Source | 2025-12-17 18:57:03 |
| 40 | openai/whisper-medium | 123.18 | 99.95 | 111.57 | Open Source | 2025-12-14 13:25:49 |
Legend:
๐ = 1st Place | ๐ฅ = 2nd Place | ๐ฅ = 3rd Place
Open Source = Model available on HuggingFace (click name to visit)
Proprietary = Closed source model
๐ = 1st Place | ๐ฅ = 2nd Place | ๐ฅ = 3rd Place
Open Source = Model available on HuggingFace (click name to visit)
Proprietary = Closed source model
Citation
If you use the Bambara ASR benchmark for your scientific publication, or if you find the resources in this leaderboard useful, please cite our work:
@misc{diallo2025bambaraasr,
title = {Where Are We at with Automatic Speech Recognition for the Bambara Language?},
author = {Seydou Diallo and Yacouba Diarra and Mamadou K. Keita and Panga Azazia Kamate and Adam Bouno Kampo and Aboubacar Ouattara},
year = {2025},
eprint = {2602.09785},
archivePrefix = {arXiv},
primaryClass = {cs.CL},
url = {https://arxiv.org/abs/2602.09785}
}
A collaboration between MALIBA-AI, RobotsMali AI4D-LAB, and Djelia
Advancing Speech Recognition Technology for African Languages