Feasibility of Real-Time Selection of Frequency Tables in an Acoustic Simulation of a Cochlear Implant

Abstract

Objectives Perception of spectrally degraded speech is particularly difficult when the signal is also distorted along the frequency axis. This might be particularly important for post-lingually deafened recipients of cochlear implants (CI), who must adapt to a signal where there may be a mismatch between the frequencies of an input signal and the characteristic frequencies of the neurons stimulated by the CI. However, there is a lack of tools that can be used to identify whether an individual has adapted fully to a mismatch in the frequency-to-place relationship and if so, to find a frequency table that ameliorates any negative effects of an unadapted mismatch. The goal of the proposed investigation is to test the feasibility of whether real-time selection of frequency tables can be used to identify cases in which listeners have not fully adapted to a frequency mismatch. The assumption underlying this approach is that listeners who have not adapted to a frequency mismatch will select a frequency table that minimizes any such mismatches, even at the expense of reducing the information provided by this frequency table. Design 34 normal-hearing adults listened to a noise-vocoded acoustic simulation of a cochlear implant and adjusted the frequency table in real time until they obtained a frequency table that sounded “most intelligible” to them. The use of an acoustic simulation was essential to this study because it allowed us to explicitly control the degree of frequency mismatch present in the simulation. None of the listeners had any previous experience with vocoded speech, in order to test the hypothesis that the real-time selection procedure could be used to identify cases in which a listener has not adapted to a frequency mismatch. After obtaining a self-selected table, we measured CNC word-recognition scores with that self-selected table and two other frequency tables: a “frequency-matched” table that matched the analysis filters with the noisebands of the noise-vocoder simulation, and a “right information” table that is similar to that used in most cochlear implant speech processors, but in this simulation results in a frequency shift equivalent to 6.5 mm of cochlear space. Results Listeners tended to select a table that was very close to, but shifted slightly lower in frequency from the frequency-matched table. The real-time selection process took on average 2–3 minutes for each trial, and the between-trial variability was comparable to that previously observed with closely-related procedures. The word-recognition scores with the self-selected table were clearly higher than with the right-information table and slightly higher than with the frequency-matched table. Conclusions Real-time self-selection of frequency tables may be a viable tool for identifying listeners who have not adapted to a mismatch in the frequency-to-place relationship, and to find a frequency table that is more appropriate for them. Moreover, the small but significant improvements in word-recognition ability observed with the sel...

Variables that Effect Psychophysical Parameters and Duration to Stability in Cochlear Implant Mapping

“…Fusion of the sound information can take time, although how long is needed is undefined. There has been a suggestion that new mapping procedures and signal processing strategies are needed, for the second implant in bilateral implantation, to allow for better fusion between them [33][34][35]. Another potential for delay in the second side is that electrodes mapped to the same frequency range in each ear may stimulate different locations in each cochlea due to an insertion depth difference of each electrode array.…”

Effect of frequency mismatch and band partitioning on vocal tract length perception in vocoder simulations of cochlear implant processing

“…The parameters for band partitioning were determined based on previous work on optimizing frequency band partitioning for a range of tasks (e.g., Shannon, 2004, 2005;Fitzgerald et al, 2013;Shannon, 1999b, 2002;McKay and Henshall, 2002;Shannon et al, 1998). The maps used in those studies (replotted in the Appendix) varied between either a logarithmic-like (Greenwood-like) partitioning or a purely linear partitioning.…”

“…In experiment 1, the synthesis filters were derived from the analysis filters by basally shifting all the frequencies by 0, 2, 4, and 6 mm relative to a 35-mm-long cochlea (Başkent and Shannon, 2005;Finley et al, 2008;Fitzgerald et al, 2013;Fu and Shannon, 1999b), as shown in panel 1 of Fig. 2.…”

“…However, in clinical practice, the frequency band partitioning maps are seldom customized for each individual CI user (Fitzgerald et al, 2013;Landsberger et al, 2015;Tan et al, 2017;Venail et al, 2015). A number of studies have suggested optimizing the frequency band partitioning map in implant processing to help alleviate the negative effects of frequency mismatch, and hence improve performance on a number of tasks, such as melodic pitch perception (Di Nardo et al, 2011;Omran et al, 2011), phoneme recognition Shannon, 1999a, 2002;Leigh et al, 2004;McKay and Henshall, 2002), and speech intelligibility (Fitzgerald et al, 2013;Grasmeder et al, 2014;McKay and Henshall, 2002).…”

“…These vocoder simulations (Dudley, 1939;Fu and Shannon, 1999b;Gaudrain and Başkent, 2015;Shannon et al, 1995;Shannon et al, 1998) were used to better specify the parameters in each frequency mismatch and band partitioning setup, as these would be difficult to control for in actual CI users (Fitzgerald et al, 2013). Just-noticeable-differences (JNDs) for VTL were collected as a measure of sensitivity following the protocol described by Başkent (2015, 2018).…”