Applied principles of clear and Lombard speech for automated intelligibility enhancement in noisy environments

Abstract

Previous studies have documented phenomena involving the modification of human speech in special communication circumstances. Whether speaking to a hearing-impaired person (clear speech) or in a noisy environment (Lombard speech), speakers tend to make similar modifications to their normal, conversational speaking style in order to increase the understanding of their message by the listener. One strategy characteristic of the above speech types is to increase consonant power relative to the signal power of adjacent vowels and is referred to as consonant–vowel (CV) ratio boosting. An automated method of speech enhancement using CV ratio boosting is called energy redistribution voiced/unvoiced (ERVU). To characterize the performance of ERVU, 25 listeners responded to 500 words in a two-word, forced-choice experiment in the presence of energetic masking noise. The test material was a vocabulary of confusable monosyllabic words spoken by 8 male and 8 female speakers, and the conditions tested were a control (unmodified speech), ERVU, and a high-pass filter (HPF). Both ERVU and the HPF significantly increased recognition accuracy compared to the control. Nine of the 16 speakers were significantly more intelligible when ERVU or the HPF was used, compared to the control, while no speaker was less intelligible. The results show that ERVU successfully increased intelligibility of speech using a simple automated segmentation algorithm, applicable to a wide variety of communication systems such as cell phones and public address systems.