Optimal gain control step sizes for bimodal stimulation.

OBJECTIVE: Cochlear implants (CI) and hearing aids (HA) have a gain control that allows the bimodal user to change the loudness. Due to differences in dynamic range between CI and HA, an equal change of the gains of the two devices results in different changes in loudness. The objective was to relate and individualise the step sizes of the loudness controls to obtain a similar perceptual effect in the two ears. DESIGN: We used loudness models parametrised for individual users to find a relation between the controls of the CI and the HA such that each step resulted in an equal change in loudness. We conducted loudness balancing experiments to validate the results. STUDY SAMPLE: Eleven bimodal users of whom six were tested in a prior study. RESULTS: The difference between the optimal gain from the loudness balancing procedure and actual gain was 3.3 dB when the new relation was applied. In contrast, the difference was 8 dB if equal step sized were applied at both sides. CONCLUSION: We can relate the controls such that each step results in a similar loudness difference.

Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users.

Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in noise for CI users. The algorithm decomposes the noisy speech signal into time-frequency units, extracts a set of auditory-inspired features and feeds them to the neural network to produce an estimation of which frequency channels contain more perceptually important information (higher signal-to-noise ratio, SNR). This estimate is used to attenuate noise-dominated and retain speech-dominated CI channels for electrical stimulation, as in traditional n-of-m CI coding strategies. The proposed algorithm was evaluated by measuring the speech-in-noise performance of 14 CI users using three types of background noise. Two NNSE algorithms were compared: a speaker-dependent algorithm, that was trained on the target speaker used for testing, and a speaker-independent algorithm, that was trained on different speakers. Significant improvements in the intelligibility of speech in stationary and fluctuating noises were found relative to the unprocessed condition for the speaker-dependent algorithm in all noise types and for the speaker-independent algorithm in 2 out of 3 noise types. The NNSE algorithms used noise-specific neural networks that generalized to novel segments of the same noise type and worked over a range of SNRs. The proposed algorithm has the potential to improve the intelligibility of speech in noise for CI users while meeting the requirements of low computational complexity and processing delay for application in CI devices.

Adjustments of the amplitude mapping function: Sensitivity of cochlear implant users and effects on subjective preference and speech recognition.

OBJECTIVE: In sound processors of cochlear implant (CI) users, input sound signals are analysed in multiple frequency channels. The amplitude mapping function (AMF) is the output compression function dictating the conversion from (acoustical) channel output levels to (electrical) current levels used for electrode stimulation. This study focused on the detectability of AMF adjustments by CI users and the effects of detectable AMF adjustments on subjective preference and performance. DESIGN: Just noticeable differences (JNDs) for AMF settings were measured for pre-processed sentences at 60 dB SPL in quiet and noise. Three AMF settings, ranging twice the JND, were used during a take-home trial period of 12 days. Subjective ratings were collected and speech recognition in quiet and noise was measured. STUDY SAMPLE: JND measurements: 17 CI users. Field experiment: 15 CI users. RESULTS: JNDs for AMF settings varied among subjects and were similar in quiet and noise. A steeper AMF in the lower part was advantageous for speech recognition in quiet at soft levels. Subjective ratings showed limited agreement with speech recognition, both in quiet and noise. CONCLUSIONS: CI users may benefit from different AMF settings in different listening situations regarding subjective preference and speech perception, especially for speech in quiet.

Music mixing preferences of cochlear implant recipients: a pilot study.

OBJECTIVE: Music perception and appraisal are generally poor in cochlear implant recipients. Simple musical structures, lyrics that are easy to follow, and clear rhythm/beat have been reported among the top factors to enhance music enjoyment. The present study investigated the preference for modified relative instrument levels in music with normal-hearing and cochlear implant subjects. DESIGN: In experiment 1, test subjects were given a mixing console and multi-track recordings to determine their most enjoyable audio mix. In experiment 2, a preference rating experiment based on the preferred relative level settings in experiment 1 was performed. STUDY SAMPLE: Experiment 1 was performed with four postlingually deafened cochlear implant subjects, experiment 2 with ten normal-hearing and ten cochlear implant subjects. RESULTS: A significant difference in preference rating was found between normal-hearing and cochlear implant subjects. The latter preferred an audio mix with larger vocals-to-instruments ratio. In addition, given an audio mix with clear vocals and attenuated instruments, cochlear implant subjects preferred the bass/drum track to be louder than the other instrument tracks. CONCLUSIONS: The original audio mix in real-world music might not be suitable for cochlear implant recipients. Modifying the relative instrument level settings potentially improves music enjoyment.

Understanding the effect of noise on electrical stimulation sequences in cochlear implants and its impact on speech intelligibility.

The present study investigates the most important factors that limit the intelligibility of the cochlear implant (CI) processed speech in noisy environments. The electrical stimulation sequences provided in CIs are affected by the noise in the following three manners. First of all, the natural gaps in the speech are filled, which distorts the low-frequency ON/OFF modulations of the speech signal. Secondly, speech envelopes are distorted to include modulations of both speech and noise. Lastly, the N-of-M type of speech coding strategies may select the noise dominated channels instead of the dominant speech channels at low signal-to-noise ratio's (SNRs). Different stimulation sequences are tested with CI subjects to study how these three noise effects individually limit the intelligibility of the CI processed speech. Tests are also conducted with normal hearing (NH) subjects using vocoded speech to identify any significant differences in the noise reduction requirements and speech distortion limitations between the two subject groups. Results indicate that compared to NH subjects CI subjects can tolerate significantly lower levels of steady state speech shaped noise in the speech gaps but at the same time can tolerate comparable levels of distortions in the speech segments. Furthermore, modulations in the stimulus current level have no effect on speech intelligibility as long as the channel selection remains ideal. Finally, wrong maxima selection together with the introduction of noise in the speech gaps significantly degrades the intelligibility. At low SNRs wrong maxima selection introduces interruptions in the speech and makes it difficult to fuse noisy and interrupted speech signals into a coherent speech stream.