Speech Understanding Performance of Cochlear Implant Subjects Using Time-Frequency Masking-Based Noise Reduction

• Published in: IEEE transactions on biomedical engineering Vol. 59; no. 5; pp. 1364 - 1373
• Main Authors: Qazi, Obaid ur Rehman, van Dijk, Bas, Moonen, Marc, Wouters, Jan
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.05.2012; Institute of Electrical and Electronics Engineers
• Subjects: Adult; Algorithms; Applied sciences; Cochlear Implants; Cochlear implants (CIs); Computer Simulation; Detection, estimation, filtering, equalization, prediction; Ear; Exact sciences and technology; Female; Humans; Information, signal and communications theory; Microphones; Middle Aged; Noise reduction; phase error variance; Phonetics; Signal and communications theory; Signal processing; Signal Processing, Computer-Assisted; Signal to noise ratio; Signal, noise; Speech; Speech Perception; Speech processing; Telecommunications and information theory; Time frequency analysis; time-frequency (TF) masking; Performance evaluation; Human; Noise reduction; time―frequency (TF) masking; Cochlear implants (CIs); phase error variance; Speech recognition; Signal processing; Cochlear implant; Masking; Phase error; Speech processing; Biomedical engineering
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2012.2187650

Cochlear implant (CI) recipients report severe degradation of speech understanding under noisy conditions. Most CI recipients typically can require about 10-25 dB higher signal-to-noise ratio than normal hearing (NH) listeners in order to achieve similar speech understanding performance. In recent years, significant emphasis has been put on binaural algorithms, which not only make use of the head shadow effect, but also have two or more microphone signals at their disposal to generate binaural inputs. Most of the CI recipients today are unilaterally implanted but they can still benefit from the binaural processing utilizing a contralateral microphone. The phase error filtering (PEF) algorithm tries to minimize the phase error variance utilizing a time-frequency mask for noise reduction. Potential improvement in speech intelligibility offered by the algorithm is evaluated with four different kinds of mask functions. The study reveals that the PEF algorithm which uses a contralateral microphone but unilateral presentation provides considerable improvement in intelligibility for both NH and CI subjects. Further, preference rating test suggests that CI subjects can tolerate higher levels of distortions than NH subjects, and therefore, more aggressive noise reduction for CI recipients is possible.