Speech Enhancement with Adaptive Thresholding and Kalman Filtering

Speech enhancement has been extensively studied for many years and various speech enhance- ment methods have been developed during the past decades. One of the objectives of speech en- hancement is to provide high-quality speech communication in the presence of background noise and concurrent interference signals. In the process of speech communication, the clean speech sig- nal is inevitably corrupted by acoustic noise from the surrounding environment, transmission media, communication equipment, electrical noise, other speakers, and other sources of interference. These disturbances can significantly degrade the quality and intelligibility of the received speech signal. Therefore, it is of great interest to develop efficient speech enhancement techniques to recover the original speech from the noisy observation. In recent years, various techniques have been developed to tackle this problem, which can be classified into single channel and multi-channel enhancement approaches. Since single channel enhancement is easy to implement, it has been a significant field of research and various approaches have been developed. For example, spectral subtraction and Wiener filtering, are among the earliest single channel methods, which are based on estimation of the power spectrum of stationary noise. However, when the noise is non-stationary, or there exists music noise and ambient speech noise, the enhancement performance would degrade considerably. To overcome this disadvantage, this thesis focuses on single channel speech enhancement under adverse noise environment, especially the non-stationary noise environment. Recently, wavelet transform based methods have been widely used to reduce the undesired background noise. On the other hand, the Kalman filter (KF) methods offer competitive denoising results, especially in non-stationary environment. It has been used as a popular and powerful tool for speech enhancement during the past decades. In this regard, a single channel wavelet thresholding based Kalman filter (KF) algorithm is proposed for speech enhancement in this thesis. The wavelet packet (WP) transform is first applied to the noise corrupted speech on a frame-by-frame basis, which decomposes each frame into a number of subbands. A voice activity detector (VAD) is then designed to detect the voiced/unvoiced frames of the subband speech. Based on the VAD result, an adaptive thresholding scheme is applied to each subband speech followed by the WP based reconstruction to obtain the pre-enhanced speech. To achieve a further level of enhancement, an iterative Kalman filter (IKF) is used to process the pre-enhanced speech. The proposed adaptive thresholding iterative Kalman filtering (AT-IKF) method is evaluated and compared with some existing methods under various noise conditions in terms of segmental SNR and perceptual evaluation of speech quality (PESQ) as two well-known performance indexes. Firstly, we compare the proposed adaptive thresholding (AT) scheme with three other threshold- ing schemes: the non-linear universal thresholding (U-T), the non-linear wavelet packet transform thresholding (WPT-T) and the non-linear SURE thresholding (SURE-T). The experimental results show that the proposed AT scheme can significantly improve the segmental SNR and PESQ for all input SNRs compared with the other existing thresholding schemes. Secondly, extensive computer simulations are conducted to evaluate the proposed AT-IKF as opposed to the AT and the IKF as standalone speech enhancement methods. It is shown that the AT-IKF method still performs the best. Lastly, the proposed ATIKF method is compared with three representative and popular meth- ods: the improved spectral subtraction based speech enhancement algorithm (ISS), the improved Wiener filter based method (IWF) and the representative subband Kalman filter based algorithm (SIKF). Experimental results demonstrate the effectiveness of the proposed method as compared to some previous works both in terms of segmental SNR and PESQ

Advanced signal processing techniques for pitch synchronous sinusoidal speech coders

Recent trends in commercial and consumer demand have led to the increasing use of multimedia applications in mobile and Internet telephony. Although audio, video and data communications are becoming more prevalent, a major application is and will remain the transmission of speech. Speech coding techniques suited to these new trends must be developed, not only to provide high quality speech communication but also to minimise the required bandwidth for speech, so as to maximise that available for the new audio, video and data services. The majority of current speech coders employed in mobile and Internet applications employ a Code Excited Linear Prediction (CELP) model. These coders attempt to reproduce the input speech signal and can produce high quality synthetic speech at bit rates above 8 kbps. Sinusoidal speech coders tend to dominate at rates below 6 kbps but due to limitations in the sinusoidal speech coding model, their synthetic speech quality cannot be significantly improved even if their bit rate is increased. Recent developments have seen the emergence and application of Pitch Synchronous (PS) speech coding techniques to these coders in order to remove the limitations of the sinusoidal speech coding model. The aim of the research presented in this thesis is to investigate and eliminate the factors that limit the quality of the synthetic speech produced by PS sinusoidal coders. In order to achieve this innovative signal processing techniques have been developed. New parameter analysis and quantisation techniques have been produced which overcome many of the problems associated with applying PS techniques to sinusoidal coders. In sinusoidal based coders, two of the most important elements are the correct formulation of pitch and voicing values from the' input speech. The techniques introduced here have greatly improved these calculations resulting in a higher quality PS sinusoidal speech coder than was previously available. A new quantisation method which is able to reduce the distortion from quantising speech spectral information has also been developed. When these new techniques are utilised they effectively raise the synthetic speech quality of sinusoidal coders to a level comparable to that produced by CELP based schemes, making PS sinusoidal coders a promising alternative at low to medium bit rates.EThOS - Electronic Theses Online ServiceGBUnited Kingdo