Abstract

The clarity enhancement challenges (CECs) seek to facilitate development of novel processing techniques for improving the intelligibility of speech in noise for hearing-aid users through a series of signal-processing challenges. Each challenge provides entrants with a set of stimuli for development and testing of their algorithms. The performance of the algorithms is assessed using objective measures of speech intelligibility and subjective measures conducted with a panel of hearing-impaired listeners. CEC2 featured more complex listening environments than CEC1 with multiple interfering sound sources (speech, music, household appliance sounds) within a simulated living-room environment at signal-to-noise ratios (SNRs) from −12 to + 4 dB. In addition, head rotation towards the target speech was introduced. Target speech came from a new dataset of 10,000 different English sentences spoken by 40 actors speaking 250 sentences each (Graetzer S et al., 2022 Data in Brief 41, 107961). The objective assessment was provided by HASPI (Kates & Arehart, 2021 Speech Comm 131, 35–46). All 18 entries achieved substantial improvements in HASPI, averaging 0.55 across all systems and SNRs. Improvements were greatest (averaging 0.61) for SNRs between −8 and 0 dB. The best-performing system achieved HASPI scores above 0.9 for all SNRs. Listening-test data will be reported.

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