A wavelet based speech enhancement method using noise classification and shaping
نویسندگان
چکیده
Speech enhancement systems performing in Fourier or wavelet domain usually generate musical noise and distortion. It is possible to reduce musical noise and speech distortion by shaping residual noise. In this paper, we propose to implement a noise shaping method for a wavelet based noise reduction system. For noise shaping, we propose a noise classification method based on spectral shape of input noise. Using this classification method, we transform input noise to another noise which is more acceptable from listening point of view. Objective and subjective test results show that using noise shaping method; we obtain less distortion in speech signal in comparison to basic wavelet noise reduction system. Furthermore, listening test results illustrate that background shaped noise is less annoying.
منابع مشابه
A New Method for Speech Enhancement Based on Incoherent Model Learning in Wavelet Transform Domain
Quality of speech signal significantly reduces in the presence of environmental noise signals and leads to the imperfect performance of hearing aid devices, automatic speech recognition systems, and mobile phones. In this paper, the single channel speech enhancement of the corrupted signals by the additive noise signals is considered. A dictionary-based algorithm is proposed to train the speech...
متن کاملSpeech Enhancement using Adaptive Data-Based Dictionary Learning
In this paper, a speech enhancement method based on sparse representation of data frames has been presented. Speech enhancement is one of the most applicable areas in different signal processing fields. The objective of a speech enhancement system is improvement of either intelligibility or quality of the speech signals. This process is carried out using the speech signal processing techniques ...
متن کاملSpeech enhancement based on hidden Markov model using sparse code shrinkage
This paper presents a new hidden Markov model-based (HMM-based) speech enhancement framework based on the independent component analysis (ICA). We propose analytical procedures for training clean speech and noise models by the Baum re-estimation algorithm and present a Maximum a posterior (MAP) estimator based on Laplace-Gaussian (for clean speech and noise respectively) combination in the HMM ...
متن کاملDenoising Of Speech Signal By Classification Into Voiced, Unvoiced And Silence Region
In this paper, a speech enhancement method based on the classification of voiced, unvoiced and silence regions and using stationary wavelet transform is presented. To prevent the quality of degradation of speech during the denoising process, speech is first classified into voiced, unvoiced and silence regions. An experimentally verified criterion based on the short time energy process has been ...
متن کاملAn improved wavelet-based speech enhancement system
The problem of speech enhancement using wavelet thresholding algorithm is considered. Major problems in applying the basic algorithm are discussed and modifications are proposed to improve the method. First, we propose the use of different thresholds for different wavelet bands. Next, by employing a pause detection algorithm, noise profile is estimated and the thresholds are adapted. This enabl...
متن کامل