Institutional Repository of Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
| NeuralDPS: Neural Deterministic Plus Stochastic Model With Multiband Excitation for Noise-Controllable Waveform Generation | |
Wang, Tao1,2; Fu, Ruibo1 ; Yi, Jiangyan1; Tao, Jianhua1; Wen, Zhengqi1
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| Source Publication | IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING
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| ISSN | 2329-9290 |
| 2022 | |
| Volume | 30Pages:865-878 |
| Corresponding Author | Fu, Ruibo(ruibo.fu@nlpr.ia.ac.cn) ; Yi, Jiangyan(jiangyan.yi@nlpr.ia.ac.cn) ; Tao, Jianhua(jhtao@nlpr.ia.ac.cn) |
| Abstract | The traditional vocoders have the advantages of high synthesis efficiency, strong interpretability, and speech editability, while the neural vocoders have the advantage of high synthesis quality. To combine the advantages of two vocoders, inspired by the traditional deterministic plus stochastic model, this paper proposes a novel neural vocoder named NeuralDPS which can retain high speech quality and acquire high synthesis efficiency and noise controllability. Firstly, this framework contains four modules: a deterministic source module, a stochastic source module, a neural V/UV decision module and a neural filter module. The input required by the vocoder is just the spectral parameter, which avoids the error caused by estimating additional parameters, such as F0. Secondly, to solve the problem that different frequency bands may have different proportions of deterministic components and stochastic components, a multiband excitation strategy is used to generate a more accurate excitation signal and reduce the neural filter's burden. Thirdly, a method to control noise components of speech is proposed. In this way, the signal-to-noise ratio (SNR) of speech can be adjusted easily. Objective and subjective experimental results show that our proposed NeuralDPS vocoder can obtain similar performance with the WaveNet and it generates waveforms at least 280 times faster than the WaveNet vocoder. It is also 28% faster than WaveGAN's synthesis efficiency on a single CPU core. We have also verified through experiments that this method can effectively control the noise components in the predicted speech and adjust the SNR of speech. |
| Keyword | Vocoders Stochastic processes Neural networks Speech processing Signal to noise ratio Acoustics Speech enhancement Vocoder speech synthesis deterministic plus stochastic multiband excitation noise control |
| DOI | 10.1109/TASLP.2022.3140480 |
| WOS Keyword | SPEECH SYNTHESIS ; VOCODER |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Key Research and Development Plan of China[2020AAA0140002] ; National Natural Science Foundation of China (NSFC)[62101553] ; National Natural Science Foundation of China (NSFC)[61831022] ; National Natural Science Foundation of China (NSFC)[61901473] ; National Natural Science Foundation of China (NSFC)[61771472] ; Inria-CAS Joint Research Project[173211KYSB 20190049] |
| Funding Organization | National Key Research and Development Plan of China ; National Natural Science Foundation of China (NSFC) ; Inria-CAS Joint Research Project |
| WOS Research Area | Acoustics ; Engineering |
| WOS Subject | Acoustics ; Engineering, Electrical & Electronic |
| WOS ID | WOS:000761216400001 |
| Publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| Sub direction classification | 语音识别与合成 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/47919 |
| Collection | 模式识别国家重点实验室_智能交互 |
| Corresponding Author | Fu, Ruibo; Yi, Jiangyan; Tao, Jianhua |
| Affiliation | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China |
| First Author Affilication | Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
| Corresponding Author Affilication | Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
| Recommended Citation GB/T 7714 | Wang, Tao,Fu, Ruibo,Yi, Jiangyan,et al. NeuralDPS: Neural Deterministic Plus Stochastic Model With Multiband Excitation for Noise-Controllable Waveform Generation[J]. IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING,2022,30:865-878. |
| APA | Wang, Tao,Fu, Ruibo,Yi, Jiangyan,Tao, Jianhua,&Wen, Zhengqi.(2022).NeuralDPS: Neural Deterministic Plus Stochastic Model With Multiband Excitation for Noise-Controllable Waveform Generation.IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING,30,865-878. |
| MLA | Wang, Tao,et al."NeuralDPS: Neural Deterministic Plus Stochastic Model With Multiband Excitation for Noise-Controllable Waveform Generation".IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 30(2022):865-878. |
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