Artificial bandwidth extension for speech signals using speech recogniton

In this paper, we propose a non-realtime speech bandwidth extension method using HMM-based speech recognition and HMM-based speech synthesis. In the proposed method, first, the phoneme-state sequence is estimated from the bandlimited speech signals using the speech recognition technique. Next, for estimating spectrum envelopes of lost high-frequency components, an HMM-based speech synthesis technique generates a synthetic speech signal (spectrum sequence) according to the predicted phoneme-state sequence. Since both speech recognition and speech synthesis take into account dynamic feature vectors, we can obtain a smoothly varying spectrum sequence. For evaluating the proposed method, we conducted subjective and objective experiments. The experimental results show the effectiveness of the proposed method for bandwidth extension. However, the proposed method needs more improvement in speech quality.