Automatic Speech Recognition
Transformers
Safetensors
Yue Chinese
whisper
cantonese
romanization
jyutping
asr
liujgoj
Instructions to use Yvthyvq/Liujgoj-Cantonese-whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yvthyvq/Liujgoj-Cantonese-whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Yvthyvq/Liujgoj-Cantonese-whisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Yvthyvq/Liujgoj-Cantonese-whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("Yvthyvq/Liujgoj-Cantonese-whisper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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### 對 CanCLID/zoengjyutgaai 中mouzaakdung音頻(https://huggingface.co/datasets/CanCLID/zoengjyutgaai/tree/main/source/mouzaakdung)嘅轉錄結果:
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([MouxZaakhdungj_wisper.xlsx](https://huggingface.co/Yvthyvq/Liujgoj-Cantonese-whisper/blob/main/MouxZaakhdungj_wisper.xlsx))
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| 項目 | Liujgoj Whisper |
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| 音頻條數 | 4742 |
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| 總字符數 | 469,105 |
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| 平均每條長度 | 98.93 |
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| 含漢字嘅條數 | **827** |
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| 漢字總數 | **16,941** |
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| 空格數 | 73,786 |
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### 對 CanCLID/zoengjyutgaai 中mouzaakdung音頻(https://huggingface.co/datasets/CanCLID/zoengjyutgaai/tree/main/source/mouzaakdung)嘅轉錄結果:
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([MouxZaakhdungj_wisper.xlsx](https://huggingface.co/Yvthyvq/Liujgoj-Cantonese-whisper/blob/main/MouxZaakhdungj_wisper.xlsx))
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### Whisper vs Omni ASR 轉寫結果比較
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| 比較指標 | Whisper 轉寫結果 | Omni 轉寫結果 |
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| :--- | :--- | :--- |
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| 總轉寫樣本數 | 4,742 條 | 4,742 條 |
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| 平均文本長度 | 98.93 字元 | 102.50 字元 |
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| 完全一致率 | 0.00% (0 條) | 0.00% (0 條) |
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| 平均文本相似度 | 71.25% | 71.25% |
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| 混入漢字樣本數 | 827 條 (17.44%) | 10 條 (0.21%) |
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| 漢字總字數 | 16,941 字 | 57 字 |
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| 重複/死循環現象 | 174 條 (3.67%) | 1 條 (0.02%) |
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| 大寫字母總數 | 2,388 個 | 8,656 個 |
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