- 期刊
- OpenAccess
Noise Robust Speech Parameterization using Relative Spectra and Auditory Filterbank
並列摘要
In the present study, a new feature extraction method based on relative spectra and gammachirp auditory filterbank is proposed for robust noisy speech recognition. The relative spectra filtering are applied to the log of the output of the gammachirp filterbank which incorporates the properties of the cochlear filter in order to remove uncorrelated additive noise components. The performances of this method have been evaluated on the isolated speech word corrupted by real-world noisy environments using the continuous Gausian-Mixture density Hidden Markov Model. The evaluation of the experimental results shows that the proposed method achieves best recognition rates compared to the conventional techniques like Perceptual Linear Prediction (PLP), Linear Predictive Cepstral Coefficients (LPCC) and Mel-Frequency Cepstral Coefficients (MFCC).
延伸閱讀
- 吳金富（2011）。Speech Enhancement Using Subspace Noise Tracking Algorithm〔碩士論文，國立臺北科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0006-2701201122004200
- 廖育志（2011）。A Speech Enhancement System based on Noise Suppression and Voiced Speech Reconstruction〔碩士論文，國立清華大學〕。華藝線上圖書館。https://doi.org/10.6843/NTHU.2011.00563
- Chen, C. H. (2009). Single-channel noise reduction algorithms for speech enhancement [doctoral dissertation, National Tsing Hua University]. Airiti Library. https://doi.org/10.6843/NTHU.2009.00038
- Gupta, V. K., Chandra, M., & Sharan, S. N. (2012). Noise Minimization from Speech Signals using RLS Algorithm with Variable Forgetting Factor. Research Journal of Applied Sciences, Engineering and Technology, 4(17), 3102-3107. https://www.airitilibrary.com/Article/Detail?DocID=20407467-201209-201512070005-201512070005-3102-3107
- 許啟輝（2007）。Reference Model Weighting and Noise Variability Subspace Projection for Robust Speech Recognition〔碩士論文，國立臺北科技大學〕。華藝線上圖書館。https://doi.org/10.6841/NTUT.2007.00426