Speech recognition for intelligent TVs is not easy mainly because of the TV sound itself. Input signals for automatic speech recognition systems have a low SNR condition due to the sounds from the TV acoustic speakers near to the microphone array installed on a TV. In addition, spoken commands for TV control are usually given at a considerably far distance. This tends to cause reverberated command inputs easily corrupted by other environmental noises. To achieve successful speech recognition with the harsh inputs, a powerful noise reduction algorithm is proposed. It is a combined solution cascading Wiener filter-based acoustic echo suppression (AES) and adaptive beamforming. To obtain noise power for AES, reference noises are estimated by utilizing the input signals to the TV speakers. For evaluation, output SNRs and speech recognition rates were measured under various noisy conditions and the results of the proposed system showed significant improvements, especially for low SNR1.