Artificial speech bandwidth extension improves telephone speech intelligibility and quality in cochlear implant users

Hearing impaired persons, and particularly hearing-aid and cochlear implant (CI) users, often have difficulties communicating over the telephone. The intelligibility of classical so-called narrowband telephone speech is considerably lower than the intelligibility of face-to-face speech. This is partly because of the lack of visual cues, limited telephone bandwidth, and background noise. This work proposes to artificially extend the standard bandwidth of telephone speech to improve its intelligibility for CI users. Artificial speech bandwidth extension (ABE) is obtained through a front-end signal processing algorithm that estimates missing speech components in the high-frequency spectrum from learned data. A state-of-the-art ABE approach, which already led to superior speech quality for people with normal hearing, is used for processing telephone speech for CI users. Two different parameterizations are evaluated, one being more aggressive than the other. Nine CI users were tested with and without the proposed ABE algorithm. The experimental evaluation shows a significant improvement in speech intelligibility and speech quality over the phone for both versions of the ABE algorithm. These promising results support the potential of ABE, which could be incorporated into a commercial speech processor or a smartphone-based pre-processor that streams the telephone speech to the CI.