| The disturbance from competing speakers is a very common disturbing situation in speech communication. The human being's acoustical system can distinguish and follow the interested speech signal in several speakers' situation, and tell apart the speech that he wants. This ability of distinguishing is a special apperception capacity of the speech comprehension mechanism in the human body, that is, people have the speech separation ability, and it's called "cocktail-party problem".In the speech and acoustical signal processing area, how to imitate human's speech separation ability and separate or extract the original or interested speech from the observed speech mixtures, has become an important problem. This is also a significant research direction in robust speech signal processing, and it has very active signification to speech recognition and speech enhancement.Present speech separation methods are mostly built on the speech mixing in the noise-free situation, and are primarily classified in two large categories: Blind Source Separation (BSS) and Computational Auditory Scene Analysis (CASA). BSS is to recover the unknown independent sources from several observed mixed signals according to the signal's statistical characteristic; While CASA is to extract the interested objective speech from the speech mixture by use of acoustical apperception elements. Generally, to simplify the research work, these methods mostly concentrate on the noise-free situations. However, in the real speech communications, speech signals can inevitably be interfered by the background noise. So it is of great value and significance to resolve problem of speech separation in the noisy environment.Noisy speech mixtures involve not only the speeches of different people but also the background noise, so it is very difficult to separate the original speeches. Presently some scholars are devoting themselves to the research of noisy BSS algorithms, but the achievement is little. The difficulty in obtaining... |
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