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.

翻译：在这次研究中,我们进行了实验,研究在德国电话识别模型的基本词汇中采用文本到手机数据增强战略添加最常用的点心大写机的影响,结果,与基线模型相比,元音30模型和Const20模型显示BLEU得分增加了1个百分点以上,而总共30个模型显示BLEU得分显著下降20多分,表明电话大写机可能对模型性能产生正负影响。此外,我们确定了模型通过错误分析反复显示的错误类型。