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CampNet: Context-Aware Mask Prediction for End-to-End Text-Based Speech Editing

文献类型：期刊论文

作者Wang, Tao1,2; Yi, Jiangyan2; Fu, Ruibo2; Tao, Jianhua2; Wen, Zhengqi2
刊名IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING
出版日期2022
卷号30页码:2241-2254
关键词Speech processing Decoding Predictive models Acoustics Transfer learning Training Task analysis Coarse-to-fine decoding mask prediction one-shot learning text-based speech editing text-to-speech
ISSN号2329-9290
DOI10.1109/TASLP.2022.3190717
通讯作者Yi, Jiangyan(jiangyan.yi@nlpr.ia.ac.cn) ; Fu, Ruibo(ruibo.fu@nlpr.ia.ac.cn) ; Tao, Jianhua(jhtao@nlpr.ia.ac.cn)
英文摘要The text-based speech editor allows the editing of speech through intuitive cutting, copying, and pasting operations to speed up the process of editing speech. However, the major drawback of current systems is that edited speech often sounds unnatural due to cut-copy-paste operation. In addition, it is not obvious how to synthesize records according to a new word not appearing in the transcript. This paper first proposes a novel end-to-end text-based speech editing method called context-aware mask prediction network (CampNet), which can solve unnatural prosody in the edited region and synthesize the speech corresponding to the unseen words in the transcript. Secondly, to cover various situations of text-based speech editing, we design three text-based operations based on CampNet: deletion, insertion, and replacement. Thirdly, to synthesize the speech corresponding to long text, a word-level autoregressive generation method is proposed. Fourthly, we propose a speaker adaptation method using only one sentence for CampNet and explore the ability of few-shot learning based on CampNet, which provides a new idea for speech forgery tasks. The subjective and objective experiments on VCTK and LibriTTS datasets(1) (1) Examples of generated speech can be found at https://hairuo55.github.io/CampNet show that the speech editing results based on CampNet are better than TTS technology, manual editing, and VoCo method. We also conduct detailed ablation experiments to explore the effect of the CampNet structure on its performance. Finally, the experiment shows that speaker adaptation with only one sentence can further improve the naturalness of speech editing for one-shot learning.
WOS关键词VOCODER ; GENERATION ; STRAIGHT ; NETWORKS
资助项目Key Research Project of China[2019KD0AD01] ; National Natural Science Foundation of China[61901473] ; National Natural Science Foundation of China[62101553] ; National Natural Science Foundation of China[61831022] ; Huawei Noah's Ark Lab
WOS研究方向Acoustics ; Engineering
语种英语
WOS记录号WOS:000831126700002
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构Key Research Project of China ; National Natural Science Foundation of China ; Huawei Noah's Ark Lab
源URL[http://ir.ia.ac.cn/handle/173211/49767]  
专题模式识别国家重点实验室_智能交互
通讯作者Yi, Jiangyan; Fu, Ruibo; Tao, Jianhua
作者单位1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Tao,Yi, Jiangyan,Fu, Ruibo,et al. CampNet: Context-Aware Mask Prediction for End-to-End Text-Based Speech Editing[J]. IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING,2022,30:2241-2254.
APA Wang, Tao,Yi, Jiangyan,Fu, Ruibo,Tao, Jianhua,&Wen, Zhengqi.(2022).CampNet: Context-Aware Mask Prediction for End-to-End Text-Based Speech Editing.IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING,30,2241-2254.
MLA Wang, Tao,et al."CampNet: Context-Aware Mask Prediction for End-to-End Text-Based Speech Editing".IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 30(2022):2241-2254.

入库方式： OAI收割

来源：自动化研究所

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