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@@ -76,7 +76,7 @@ Conformer-Transducer model is an autoregressive variant of Conformer model [2] f
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  The model was finetuned based on the pre-trained English Model for over several epochs.
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- There are several transcripting and sub-word modeling methods for Korean speech recognition. This model uses sentencepiece subwords of Hangul characters based on phonetic transcription using Google Sentencepiece Tokenizer [3].
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  ### Datasets
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@@ -90,8 +90,9 @@ v1.7.0rc | SentencePiece Char | 6.94% | 7.38% | 19.49% | 22.73%
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  ## Limitations
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- Eg:
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- Since this model was trained on publically available speech datasets, the performance of this model might degrade for speech which includes technical terms, or vernacular that the model has not been trained on. The model might also perform worse for accented speech.
 
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  ## References
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  The model was finetuned based on the pre-trained English Model for over several epochs.
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+ There are several transcribing and sub-word modeling methods for Korean speech recognition. This model uses sentencepiece subwords of Hangul characters based on phonetic transcription using Google Sentencepiece Tokenizer [3].
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  ### Datasets
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  ## Limitations
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+ Since this model was trained on publically available speech datasets, the performance of this model might degrade for speech which including technical terms, or vernacular that the model has not been trained on. The model might also perform worse for accented speech.
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+ This model produces a spoken-form token sequence. If you want to have a written form, you can consider applying inverse text normalization.
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  ## References