Speaker-independent auditory attention decoding without access to clean speech sources.

ABSTRACT: Speech perception in crowded environments is challenging for hearing-impaired listeners. Assistive hearing devices cannot lower interfering speakers without knowing which speaker the listener is focusing on. One possible solution is auditory attention decoding in which the brainwaves of listeners are compared with sound sources to determine the attended source, which can then be amplified to facilitate hearing. In realistic situations, however, only mixed audio is available. We utilize a novel speech separation algorithm to automatically separate speakers in mixed audio, with no need for the speakers to have prior training. Our results show that auditory attention decoding with automatically separated speakers is as accurate and fast as using clean speech sounds. The proposed method signif

SUBMITTER: Han C 

PROVIDER: S-EPMC6520028 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature