This paper presents single-channel speech enhancement techniques in spectral domain. One of the most famous single channel speech enhancement techniques is the spectral subtraction method proposed by S.F. Boll in 1979. In this method, an estimated speech spectrum is obtained by simply subtracting a preestimated noise spectrum from an observed one. Hence, the spectral subtraction method is not concerned with speech spectral properties. It is well known that the spectral subtraction method produces an annoying artificial noise in the extracted speech signal. On the other hand, recent successful speech enhancement methods positively utilize the speech property and achieve an efficient speech enhancement capability. This paper presents a historical review about some speech estimation techniques and explicitly states the difference between their theoretical back-ground. Moreover, to evaluate their speech enhancement capabilities, we perform computer simulations. The results show that an adaptive speech enhancement method based on MAP estimation gives the best noise reduction capability in comparison to other speech enhancement methods presented in this paper. 1. Introduction In recent years, speech enhancement is required in a wide area of applications including mobile communication and speech recognition systems, where the major example is a cell-phone as shown in Figure 1. Many speech enhancement methods have been established in decades [1–15]. These speech enhancement techniques can be classified to time domain methods and spectral domain methods. Recent major speech enhancement techniques are of the spectral domain method which is preferably used in a cell phone. In this paper, we focus on the spectral domain speech enhancement techniques that employ a single microphone. Figure 1: Application of speech enhancement. The spectral subtraction method [3] is one of the most popular methods among numerous noise reduction techniques in spectral domain. This method achieves noise reduction by simply subtracting a pre-estimated noise spectral amplitude from an observed spectral amplitude, where the spectral phase is not processed. The spectral subtraction method is easy for implementation and effectively reduces stationary noises. However, it incurs an artificial noise, called musical noise, which is caused from speech estimation errors. Because the spectral subtraction method is not concerned with speech spectral information, it often gives estimation errors. Ephraim and Malah have proposed the MMSE-STSA (Minimum Mean Square Error-Short-Time Spectral Amplitude)
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