Distant-talking speech enhancement based on spectrum restoring with phoneme labels

Abstract

With the development of communication and speech recognition technology, remote conference and robot communication systems have been developed in recent years. Although these are valid in close-talking speech, distant-talking speech degrades the performance of the systems. The reason is that it is affected by energy decay, noise and reverberations depending on the distances. To solve this problem, many noise reduction and speech enhancement approaches have been proposed. In the conventional approaches, the example-based speech enhancement is one of the effective noise reduction methods in distant-talking conditions. The most similar example of noisy speech to input signal is detected from model examples of clean and noisy speech signals. Thereby it can estimate and suppress the noise based on the clean speech. Although it can effectively reduce noise, it is not clear the performance in the distant-talking speech condition with the decay of speech energy. Thus in this paper, we proposed a distant-talking speech enhancement based on spectrum restoring with phoneme labels. It restores the clean spectrum from decayed spectrum based on spectrum envelopes for each phoneme label. We demonstrate the experiment to evaluate the effectiveness of proposed method. As a result, we confirmed that it can effectively enhance the target speech.