A method of speech periodicity enhancement using transform-domain signal decomposition
| Autor: | Tan Lee, Feng Huang, W. Bastiaan Kleijn, Ying-Yee Kong |
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| Rok vydání: | 2015 |
| Předmět: |
Linguistics and Language
Dynamic time warping Computer science Communication Speech recognition Speech coding Linear prediction Filter (signal processing) Linear predictive coding Residual Signal Article Language and Linguistics Computer Science Applications Speech enhancement Computer Science::Sound Modeling and Simulation Computer Vision and Pattern Recognition Software |
| Zdroj: | Speech Communication. 67:102-112 |
| ISSN: | 0167-6393 |
| Popis: | Periodicity is an important property of speech signals. It is the basis of the signal’s fundamental frequency and the pitch of voice, which is crucial to speech communication. This paper presents a novel framework of periodicity enhancement for noisy speech. The enhancement is applied to the linear prediction residual of speech. The residual signal goes through a constant-pitch time warping process and two sequential lapped-frequency transforms, by which the periodic component is concentrated in certain transform coefficients. By emphasizing the respective transform coefficients, periodicity enhancement of noisy residual signal is achieved. The enhanced residual signal and estimated linear prediction filter parameters are used to synthesize the output speech. An adaptive algorithm is proposed for adjusting the weights for the periodic and aperiodic components. Effectiveness of the proposed approach is demonstrated via experimental evaluation. It is observed that harmonic structure of the original speech could be properly restored to improve the perceptual quality of enhanced speech. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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