论文标题
GIPFA：从音频生成IPA发音
GIPFA: Generating IPA Pronunciation from Audio
论文作者
论文摘要
长期以来，专家保留了将口头音频样品转录到国际语音字母（IPA）中。在这项研究中，我们检查了人工神经网络（ANN）模型的使用来根据其音频发音自动提取ipa的Quantic发音，因此其名称从音频产生了IPA发音（GIPFA）。根据法国Wikimedia词典，我们训练了我们的模型，然后正确预测了已测试的IPA发音的75％。有趣的是，通过研究推论错误，该模型使得可以突出数据集中可能出现的错误，并确定法语中最接近的音素。
Transcribing spoken audio samples into the International Phonetic Alphabet (IPA) has long been reserved for experts. In this study, we examine the use of an Artificial Neural Network (ANN) model to automatically extract the IPA phonemic pronunciation of a word based on its audio pronunciation, hence its name Generating IPA Pronunciation From Audio (GIPFA). Based on the French Wikimedia dictionary, we trained our model which then correctly predicted 75% of the IPA pronunciations tested. Interestingly, by studying inference errors, the model made it possible to highlight possible errors in the dataset as well as to identify the closest phonemes in French.
