Experiments in [4] showed that a combination of GPS and GLONASS navigation systems reduces root-mean-square (RMS) error by half and outliers by several times. Another solution is introducing the so-called probability map
For many antagonist Enzalutamide speech related applications such as hands-free telephony, hearing aids, video or teleconferencing, speaker identification and speech-controlled devices, recovering clean speech in noisy acoustical environment has been a difficult task for many years now. These applications require clean speech to function efficiently. In the past few decades, various algorithms have emerged aimed at reducing the background noise from the acquired speech signal. These algorithms can be single or multi-sensor methods. The idea behind most popular algorithms is to use an adaptive filter to reduce the interference signal [1].
In the adaptive noise cancellation (ANC) technique, a two-sensor model is often used for speech enhancement with the arrangement shown in Figure 1. This structure is largely used for applications where the speech signal is isolated from the reference signal, and the noise signals are correlated in both channels. It is often assumed that the two sensors, in this case microphones, are physically separated and isolated from each other, so that no substantial speech leakage into the reference input occurs, otherwise intelligibility of the speech signal will be degraded by the adaptive process. In practice, the two microphones should be located within few centimeters [2]. In the past, directional microphones and acoustic barriers are used to prevent speech leakage into the reference input [2].
Voice activity detectors VADs are offered in more advanced systems nowadays Brefeldin_A [3�C6]. The primary function of a voice activity detector is to provide an indication of speech presence, in order to facilitate speech processing as well as providing indications for the beginning and end of a speech segment. The intention of the present work is to develop a voice activity detection (VAD) system to control the operation of a two-sensor adaptive noise canceller. The use of VAD in this context has a two-fold advantage, first, the convergence behavior of the adaptive filter can be improved since the reference input will be highly correlated with the noise components in the primary input, and second, the computation power is reduced since the output of the adaptive filter will be calculated only during non-speech periods.
This power saving is of great importance in many applications such as hands-free communications, where processing power must be kept as low as possible, due to size and weight limitations.Figure 1.The two-microphone adaptive noise canceller.An example of a one-end speech of a typical telephone conversation is depicted in http://www.selleckchem.com/products/Imatinib(STI571).html Figure 2.