Hugging Face's logo

Spaces:
msalhab96
/
open_universal_arabic_asr_leaderboard_all
Running

App Files Community
Mahmoud Salhab commited on
Commit
27dc445
·
1 Parent(s): d9aee5a

adding closed source models

Browse files
Files changed (1) hide show
  1. app.py +15 -15
app.py CHANGED
@@ -51,21 +51,21 @@ LAST_UPDATED = "Jan 12th 2025:[New models included: nvidia-Parakeet-ctc-1.1b-con
51
 
52
 
53
  results = {
54
- "Model": ["nvidia-conformer-ctc-large-arabic (lm)", "nvidia-conformer-ctc-large-arabic (greedy)", "openai/whisper-large-v3", "facebook/seamless-m4t-v2-large", "openai/whisper-large-v3-turbo", "openai/whisper-large-v2", "openai/whisper-large", "asafaya/hubert-large-arabic-transcribe", "openai/whisper-medium", "nvidia-Parakeet-ctc-1.1b-concat", "nvidia-Parakeet-ctc-1.1b-universal", "facebook/mms-1b-all", "openai/whisper-small", "whitefox123/w2v-bert-2.0-arabic-4", "jonatasgrosman/wav2vec2-large-xlsr-53-arabic", "speechbrain/asr-wav2vec2-commonvoice-14-ar"],
55
- "Average WER⬇️": [32.91, 34.74, 36.86, 38.16, 40.05, 40.20, 42.57, 45.50, 45.57, 46.54, 51.96, 54.54, 55.13, 58.13, 60.98, 65.74],
56
- "Average CER": [13.84, 13.37, 17.21, 17.03, 18.87, 19.55, 20.49, 17.35, 22.27, 23.88, 25.19, 21.45, 21.68, 27.62, 25.61, 30.93],
57
- "SADA WER": [44.52, 47.26, 55.96, 62.52, 60.36, 57.46, 63.24, 67.82, 67.71, 70.70, 73.58, 77.48, 78.02, 87.34, 86.82, 88.54],
58
- "SADA CER": [23.76, 22.54, 34.62, 37.61, 37.67, 36.59, 40.16, 31.83, 43.83, 46.70, 49.48, 37.50, 33.17, 56.75, 44.20, 50.28],
59
- "Common Voice WER": [8.80, 10.60, 17.83, 21.70, 25.73, 21.77, 26.04, 8.01, 28.07, 26.34, 40.01, 26.52, 24.18, 41.79, 23.00, 29.17],
60
- "Common Voice CER": [2.77, 3.05, 5.74, 6.24, 10.89, 7.44, 9.61, 2.37, 10.38, 9.82, 14.64, 7.21, 6.79, 15.75, 6.64, 9.85],
61
- "MASC(clean-test) WER": [23.74, 24.12, 24.66, 25.04, 25.51, 27.25, 28.89, 32.94, 29.99, 30.49, 36.16, 38.82, 35.93, 37.82, 42.75, 49.10],
62
- "MASC(clean-test) CER": [5.63, 5.63, 7.24, 7.19, 7.55, 8.28, 9.05, 7.15, 8.98, 8.41, 10.29, 10.36, 9.01, 11.92, 11.87, 16.37],
63
- "MASC(noisy-test) WER": [34.29, 35.64, 34.63, 33.24, 37.16, 38.55, 40.79, 50.16, 42.91, 45.95, 50.03, 57.33, 56.36, 53.28, 64.27, 69.57],
64
- "MASC(noisy-test) CER": [11.07, 11.02, 12.89, 11.92, 13.93, 15.49, 16.31, 15.62, 17.49, 18.72, 20.09, 19.76, 19.43, 21.93, 24.17, 30.17],
65
- "MGB-2 WER": [17.20, 19.69, 16.26, 20.23, 17.75, 25.17, 24.28, 37.51, 29.32, 24.94, 30.68, 39.16, 48.64, 40.66, 56.29, 64.37],
66
- "MGB-2 CER": [6.87, 7.46, 7.74, 9.37, 8.34, 13.48, 12.10, 11.07, 14.82, 9.87, 11.36, 13.48, 15.56, 19.39, 20.44, 26.56],
67
- "Casablanca WER": [68.90, 71.13, 71.81, 66.25, 73.79, 71.01, 72.18, 76.53, 75.44, 80.80, 81.30, 87.95, 87.64, 87.88, 92.72, 93.68],
68
- "Casablanca CER": [32.97, 30.50, 35.04, 29.85, 34.83, 36.00, 35.71, 36.03, 38.12, 49.77, 45.31, 40.41, 46.12, 39.99, 46.33, 52.36],
69
  }
70
 
71
  original_df = pd.DataFrame(results)
 
51
 
52
 
53
  results = {
54
+ "Model": ["cntxt-ai-munsit-1", "elevenlabs-scribe-v1", "microsoft-azure-stt", "openai-gpt-4o-transcribe", "nvidia-conformer-ctc-large-arabic (lm)", "nvidia-conformer-ctc-large-arabic (greedy)", "openai/whisper-large-v3", "facebook/seamless-m4t-v2-large", "openai/whisper-large-v3-turbo", "openai/whisper-large-v2", "openai/whisper-large", "asafaya/hubert-large-arabic-transcribe", "openai/whisper-medium", "nvidia-Parakeet-ctc-1.1b-concat", "nvidia-Parakeet-ctc-1.1b-universal", "facebook/mms-1b-all", "openai/whisper-small", "whitefox123/w2v-bert-2.0-arabic-4", "jonatasgrosman/wav2vec2-large-xlsr-53-arabic", "speechbrain/asr-wav2vec2-commonvoice-14-ar"],
55
+ "Average WER⬇️": [26.68, 40.05, 45.72, 44.97, 32.91, 34.74, 36.86, 38.16, 40.05, 40.20, 42.57, 45.50, 45.57, 46.54, 51.96, 54.54, 55.13, 58.13, 60.98, 65.74],
56
+ "Average CER": [10.05, 14.75, 19.45, 24.31, 13.84, 13.37, 17.21, 17.03, 18.87, 19.55, 20.49, 17.35, 22.27, 23.88, 25.19, 21.45, 21.68, 27.62, 25.61, 30.93],
57
+ "SADA WER": [27.71, 49.44, 58.5, 66.47, 44.52, 47.26, 55.96, 62.52, 60.36, 57.46, 63.24, 67.82, 67.71, 70.70, 73.58, 77.48, 78.02, 87.34, 86.82, 88.54],
58
+ "SADA CER": [11.65, 23.33, 35.39, 49.57, 23.76, 22.54, 34.62, 37.61, 37.67, 36.59, 40.16, 31.83, 43.83, 46.70, 49.48, 37.50, 33.17, 56.75, 44.20, 50.28],
59
+ "Common Voice WER": [10.42, 28.27, 33.775, 28.19, 8.80, 10.60, 17.83, 21.70, 25.73, 21.77, 26.04, 8.01, 28.07, 26.34, 40.01, 26.52, 24.18, 41.79, 23.00, 29.17],
60
+ "Common Voice CER": [3.21, 7.33, 9.29, 8.14, 2.77, 3.05, 5.74, 6.24, 10.89, 7.44, 9.61, 2.37, 10.38, 9.82, 14.64, 7.21, 6.79, 15.75, 6.64, 9.85],
61
+ "MASC(clean-test) WER": [21.74, 31.93, 40.66, 31.53, 23.74, 24.12, 24.66, 25.04, 25.51, 27.25, 28.89, 32.94, 29.99, 30.49, 36.16, 38.82, 35.93, 37.82, 42.75, 49.10],
62
+ "MASC(clean-test) CER": [5.8, 8.23, 14.735, 8.85, 5.63, 5.63, 7.24, 7.19, 7.55, 8.28, 9.05, 7.15, 8.98, 8.41, 10.29, 10.36, 9.01, 11.92, 11.87, 16.37],
63
+ "MASC(noisy-test) WER": [28.08, 41.23, 45.645, 43.29, 34.29, 35.64, 34.63, 33.24, 37.16, 38.55, 40.79, 50.16, 42.91, 45.95, 50.03, 57.33, 56.36, 53.28, 64.27, 69.57],
64
+ "MASC(noisy-test) CER": [8.88, 13.14, 15.77, 18.81, 11.07, 11.02, 12.89, 11.92, 13.93, 15.49, 16.31, 15.62, 17.49, 18.72, 20.09, 19.76, 19.43, 21.93, 24.17, 30.17],
65
+ "MGB-2 WER": [12.1, 25.68, 30.91, 29.62, 17.20, 19.69, 16.26, 20.23, 17.75, 25.17, 24.28, 37.51, 29.32, 24.94, 30.68, 39.16, 48.64, 40.66, 56.29, 64.37],
66
+ "MGB-2 CER": [5.27, 9.27, 13.7, 17.34, 6.87, 7.46, 7.74, 9.37, 8.34, 13.48, 12.10, 11.07, 14.82, 9.87, 11.36, 13.48, 15.56, 19.39, 20.44, 26.56],
67
+ "Casablanca WER": [60.04, 63.77, 64.84, 70.72, 68.90, 71.13, 71.81, 66.25, 73.79, 71.01, 72.18, 76.53, 75.44, 80.80, 81.30, 87.95, 87.64, 87.88, 92.72, 93.68],
68
+ "Casablanca CER": [25.51, 27.17, 27.84, 43.15, 32.97, 30.50, 35.04, 29.85, 34.83, 36.00, 35.71, 36.03, 38.12, 49.77, 45.31, 40.41, 46.12, 39.99, 46.33, 52.36],
69
  }
70
 
71
  original_df = pd.DataFrame(results)