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README.md
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- **PER:** 0.49
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- **GER:** 0.39
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- **PER:** 0.49
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**Note:** CUPE models are designed for contextless phoneme prediction and are not optimal for phoneme classification tasks that require contextual information. For lower Phoneme Error Rate (PER) metrics, consider using large-scale pretrained models that process entire utterances with contextual awareness. CUPE excels at extracting pure, frame-level embeddings that represent the acoustic properties of each phoneme (e.g., /a/) independently of surrounding context.
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