Cochlear implants (CIs) are surgically implanted electronic devices that provide a sense of sound in patients with profound to severe hearing loss. The considerable progress of CI technologies in the past three decades has enabled many CI users to enjoy a high level of speech understanding in quiet. For most CI users, however, understanding speech in noisy environments remains a challenge. In this talk, I will present the deep learning based noise reduction (NR) approach, which has been demonstrated its effectiveness for improving the speech intelligibility for CI recipients. Experimental results indicated that deep learning based NR yields higher intelligibility scores than conventional approaches for Mandarin-speaking listeners, suggesting that DDAE NR could potentially be integrated into a CI processor to overcome speech perception degradation caused by noise.