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In this work we evaluate a neural based speech intelligibility booster basedon spectral shaping and dynamic range compression (SSDRC), referred to asWaveNet-based SSDRC (wSSDRC), using a recently designed Greek Harvard-stylecorpus. The corpus has been developed according to the format of theHarvard/IEEE sentences and offers the opportunity to apply neural speechenhancement models and examine their performance gain for Greek listeners.wSSDRC has been successfully tested for English material and speakers in thepast. In this paper we revisit wSSDRC to perform a full scale evaluation of themodel with Greek listeners under the condition of equal energy before and aftermodification. Both normal hearing (NH) and hearing impaired (HI) listenersevaluated the model under speech shaped noise (SSN) at listener-specific SNRsmatching their Speech Reception Threshold (SRT) - a point at which 50 % ofunmodified speech is intelligible. The analysis statistics show that the wSSDRCmodel has produced a median intelligibility boost of 39% for NH and 38% for HI,relative to the plain unprocessed speech.

Evaluating the Intelligibility Benefits of Neural Speech Enrichment for  Listeners with Normal Hearing and Hearing Impairment using the Greek Harvard  Corpus