In the narrowband speech communication system, one of the impotant problems is that making use of the limited bandwidth resource to enhance and transmit speech signal in complex environment in order to improving the speech quality. There are all kinds of noise in real environment; it is urgent to solve the problem which is detecting the speech signal accurately and separating the speech signal in noise background efficiently. Many of mainstream speech enhancement algorithms are difficult to estimate the speech signal accurately especially in non stationary noise environment and the enhanced speech cann’t meet the requirement. There is some limitation of bit resource and bandwidth in some special narrowband communication channels and the speech signal has to transmit at very low bit rate. Therefore, it is impotant to design the very low bit rate speech coding algorithm which could applid to wireless communication system and underwater acoustic communication system; however, the speech quality will be worse with the decreasing of speech coding rate. In addition, the spectra information of the high-band will lose in narrowband communication channel and it will lead to the decreasing of speech naturalness. It is significant to do some research on improving the speech quality of narrowband speech communication system in real environment and it is also a large chanllenge topic. To solve above mentioned problems existing in narrowband speech communication system, this thesis focus on researching deeply speech quality enhancement in narrowband speech communication system. The research content and innovation points are as follows. A robust speech activity detection algorithm is proposed in noise environment. The sub-band temporal envelope and the sub-band long-term signal variability are combined to distinguish the speech segment from the non speech segment in noise environment. To improve the performance, the sub-band which could reflect the formant characteristic is selected to extract both of features. This is a low complexity and unsupervised speech activity detection algorithm; there is no pre-training model. The experiment result shows that the proposed speech acitivity detection algorithm is prior to different baseline methods in different environment and it could be applied in speech communication system. A single channel speech enhancement algorithm based on analysis-synthesis framework is proposed. An improved pitch detection algorithm based on multi...
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