TY - GEN
T1 - CHINESE SPELLING TEXT GENERATION OF MATHEMATICAL FORMULAS
AU - Dong, Su
AU - Liu, Shan
AU - Liu, Sicen
AU - Tang, Buzhou
N1 - Publisher Copyright:
© 2022 IEEE
PY - 2022
Y1 - 2022
N2 - Recently, speech assistants have brought convenience to our lives from many aspects. In the education field, speech assistants can also help teachers to reduce their burdens. However, there is no suitable solution to synthesize speeches for mathematical formulas although there have been lots of good techniques for text-to-speech (TTS) in the general domain. One possible solution is that we can convert mathematical formulas expressed in the LaTeX format to spelling texts and synthesize them into speech. In this paper, we investigated text generation methods that translate mathematical formulas in LaTex into Chinese spelling texts. For this purpose, we first constructed a parallel corpus of mathematical formulas and Chinese spelling texts, then compared the existing commonly used text generation methods, such as rule-based, Seq2Seq, Transformer and Graph2Seq, and finally proposed a novel model. As far as we know, this is the first study for Chinese spelling text generation of mathematical formulas. Experiment results on the annotated corpus show that our proposed model significantly outperforms the existing commonly used generation models.
AB - Recently, speech assistants have brought convenience to our lives from many aspects. In the education field, speech assistants can also help teachers to reduce their burdens. However, there is no suitable solution to synthesize speeches for mathematical formulas although there have been lots of good techniques for text-to-speech (TTS) in the general domain. One possible solution is that we can convert mathematical formulas expressed in the LaTeX format to spelling texts and synthesize them into speech. In this paper, we investigated text generation methods that translate mathematical formulas in LaTex into Chinese spelling texts. For this purpose, we first constructed a parallel corpus of mathematical formulas and Chinese spelling texts, then compared the existing commonly used text generation methods, such as rule-based, Seq2Seq, Transformer and Graph2Seq, and finally proposed a novel model. As far as we know, this is the first study for Chinese spelling text generation of mathematical formulas. Experiment results on the annotated corpus show that our proposed model significantly outperforms the existing commonly used generation models.
KW - Mathematical Formals to Chinese spelling texts
KW - text generation
KW - text-to-speech
UR - https://www.scopus.com/pages/publications/85131265132
U2 - 10.1109/ICASSP43922.2022.9747049
DO - 10.1109/ICASSP43922.2022.9747049
M3 - 会议稿件
AN - SCOPUS:85131265132
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 7127
EP - 7131
BT - 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2022
Y2 - 22 May 2022 through 27 May 2022
ER -