@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00230179,
 author = {李, 在詠 and 三村, 正人 and 河原, 達也},
 book = {第85回全国大会講演論文集},
 issue = {1},
 month = {Feb},
 note = {A method using explicit prior knowledge about phonemes is presented for improving automatic speech recognition (ASR) performance in low resource settings. First, a fixed-length encoding is defined for each phoneme, where each element of the encoding represents a distinct phonetic feature. Second, a phonetic feature prediction layer is put in a deep neural network (DNN) and the feature predictions are used to make the final token predictions. Experiments are conducted in multilingual settings where Ainu is the target low-resource language. Effectiveness and robustness of this method is explored with varying amounts of training data.},
 pages = {787--788},
 publisher = {情報処理学会},
 title = {音素に関する事前知識を埋め込んだアイヌ語 End-to-end 音声認識},
 volume = {2023},
 year = {2023}
}