Beamforming and Single-Microphone Noise Reduction: Effects on Signal-to-Noise Ratio and Speech Recognition of Bimodal Cochlear Implant Users

Abstract

We have investigated the effectiveness of three noise-reduction algorithms, namely an adaptive monaural beamformer (MB), a fixed binaural beamformer (BB), and a single-microphone stationary-noise reduction algorithm (SNRA) by assessing the speech reception threshold (SRT) in a group of 15 bimodal cochlear implant users. Speech was presented frontally towards the listener and background noise was established as a homogeneous field of long-term speech-spectrum-shaped (LTSS) noise or 8-talker babble. We pursued four research questions, namely: whether the benefits of beamforming on the SRT differ between LTSS noise and 8-talker babble; whether BB is more effective than MB; whether SNRA improves the SRT in LTSS noise; and whether the SRT benefits of MB and BB are comparable to their improvement of the signal-to-noise ratio (SNR). The results showed that MB and BB significantly improved SRTs by an average of 2.6 dB and 2.9 dB, respectively. These benefits did not statistically differ between noise types or between the two beamformers. By contrast, physical SNR improvements obtained with a manikin revealed substantially greater benefits of BB (6.6 dB) than MB (3.3 dB). SNRA did not significantly affect SRTs per se in omnidirectional microphone settings, nor in combination with MB and BB. We conclude that in the group of bimodal listeners tested, BB had no additional benefits on speech recognition over MB in homogeneous noise, despite the finding that BB had a substantial larger benefit on the SNR than MB. SNRA did not improve speech recognition.