German Phoneme Recognition with Text-to-Phoneme Data Augmentation
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Abstract (arXiv)
In this study, we experimented to examine the effect of adding the most frequent n phoneme bigrams to the basic vocabulary on the German phoneme recognition model using the text-to-phoneme data augmentation strategy. As a result, compared to the baseline model, the vowel30 model and the const20 model showed an increased BLEU score of more than 1 point, and the total30 model showed a significant decrease in the BLEU score of more than 20 points, showing that the phoneme bigrams could have a positive or negative effect on the model performance. In addition, we identified the types of errors that the models repeatedly showed through error analysis.
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References · 2
- 2017Attention Is All You Needcited by 60,361
- 2019CSS10: A Collection of Single Speaker Speech Datasets for 10 Languagescited by 54
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