Papers by Yanjun Ma
PaddleSpeech: An Easy-to-Use All-in-One Speech Toolkit (2022.naacl-demo)
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Hui Zhang, Tian Yuan, Junkun Chen, Xintong Li, Renjie Zheng, Yuxin Huang, Xiaojie Chen, Enlei Gong, Zeyu Chen, Xiaoguang Hu, Dianhai Yu, Yanjun Ma, Liang Huang
| Challenge: | PaddleSpeech is an open-source speech toolkit that supports speech-to-text and text-to speech tasks. |
| Approach: | They describe the design philosophy and core architecture of PaddleSpeech to support several essential speech-to-text and text-to speech tasks. |
| Outcome: | The proposed framework achieves competitive or state-of-the-art performance on various speech datasets and implements the most popular methods. |
A Gentle Introduction to Deep Nets and Opportunities for the Future (2022.acl-tutorials)
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| Challenge: | a tutorial on deep nets will introduce a new language for fine tuning deep net programs . the tutorial will be divided into two parts: Part A will make deep net programming accessible to a broader audience . |
| Approach: | This tutorial introduces a new language for fine tuning deep nets with short (1-line) programs that are as easy to code as regression in statistics packages such as R. |
| Outcome: | This tutorial will introduce gft (general fine tuning), a new language for deep nets . glm is a "little language" similar to gslm in statistics package R . |
Answer-focused and Position-aware Neural Question Generation (D18-1)
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| Challenge: | Recent neural network-based approaches generate interrogative words that do not match the answer type. |
| Approach: | They propose an answer-focused and position-aware neural question generation model to address these issues. |
| Outcome: | The proposed model outperforms the baseline and outperformed the state-of-the-art system. |