Ladoshko O. Robustness enhancement of automatic speech recognition systems by signal processing techniques

The goal of thesis: development of speech enhancement and robust feature extraction methods for robust automatic speech recognition. Modification of existing logMMSE methods have proposed. It is used instead of noise spectrum estimator for enhancement of speech distorted by reverberation. Neural network based voice activity detector for automatic speech recognition system have proposed. It is enabling the use of robust features power normalized cepstral coefficients with non-stationary noise. It had been proposed to include as a classification feature trajectory of the pitch. For this purpose, it had been proposed the use of pitch tracking algorithm in noisy speech. Adaptive correction parameters algorithm of neural network based voice activity detector had been proposed to accelerate the learning process. The proposed approach also outperforms other state-of-the-art voice activity detection algorithms.