The Advanced Combination Encoder (ACE) signal processing strategy is used in the majority of cochlear implant (CI) sound processors manufactured by Cochlear Corporation. This “n-of-m” strategy selects “n” out of “m” available frequency channels with the highest spectral energy in each stimulation cycle. It is hypothesized that at low signal-to-noise ratio (SNR) conditions, noise–dominant frequency channels are susceptible for selection, neglecting channels containing target speech cues. In order to improve speech segregation in noise, explicit encoding of formant frequency locations within the standard channel selection framework of ACE is suggested. Two strategies using the direct formant estimation algorithms are developed within this study, FACE (formant-ACE) and VFACE (voiced-activated-formant-ACE). Speech intelligibility from eight CI users is compared across 11 acoustic conditions, including mixtures of noise and reverberation at multiple SNRs. Significant intelligibility gains were observed with VFACE over ACE in 5 dB babble noise; however, results with FACE/VFACE in all other conditions were comparable to standard ACE. An increased selection of channels associated with the second formant frequency is observed for FACE and VFACE. Both proposed methods may serve as potential supplementary channel selection techniques for the ACE sound processing strategy for cochlear implants.

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