The effect of reduced dynamic range on speech understanding: implications for patients with cochlear implants.

OBJECTIVE: To determine the effect of reduced dynamic range on speech understanding when the speech signals are processed in a manner similar to a 6-channel cochlear implant speech processor. DESIGN: Signals were processed in a manner similar to a 6-channel cochlear implant processor and output as a sum of sine waves with frequencies equal to the center frequencies of the analysis filters. The amplitudes of the sine waves were compressed in a systematic fashion to simulate the effect of reduced dynamic range. The compressed signals were presented to 10 normal-hearing listeners for identification. RESULTS: There was a significant effect of compression for all test materials. The effect of the compression on speech understanding was different for the three test materials (vowels, consonants, and sentences). Vowel recognition was affected the most by the compression, and consonant recognition was affected the least by the compression. Feature analysis indicated that the reception of place information was affected the most. Sentence recognition was moderately affected by the compression. CONCLUSIONS: Dynamic range should affect the speech perception abilities of cochlear implant users. Our results suggest that a relatively wide dynamic range is needed for a high level of vowel recognition and a relatively small dynamic range is sufficient to maintain consonant recognition. We infer from this outcome that, if other factors were held equal, an implant patient with a small dynamic range could achieve moderately high scores on tests of consonant recognition but poor performance on vowel recognition, and that it is more likely for an implant patient with a large dynamic range to obtain high scores on vowel recognition than for an implant patient with a small dynamic range.

Recognition of sentences in noise by normal-hearing listeners using simulations of speak-type cochlear implant signal processors.

To assess whether more channels are needed to understand speech in noise than in quiet, we processed speech in a manner similar to that of spectral peak-like cochlear implant processors and presented it at a +2-dB signal-to-noise ratio to normal-hearing listeners for identification. The number of analysis filters varied from 8 to 16, and the number of maximum channel amplitudes selected in each cycle varied from 2 to 16. The results show that more channels are needed to understand speech in noise than in quiet, and that high levels of speech understanding can be achieved with 12 channels. Selecting more than 12 channel amplitudes out of 16 channels did not yield significant improvements in recognition performance.

The recognition of sentences in noise by normal-hearing listeners using simulations of cochlear-implant signal processors with 6-20 channels.

Sentences were processed through simulations of cochlear-implant signal processors with 6, 8, 12, 16, and 20 channels and were presented to normal-hearing listeners at +2 db S/N and at -2 db S/N. The signal-processing operations included bandpass filtering, rectification, and smoothing of the signal in each band, estimation of the rms energy of the signal in each band (computed every 4 ms), and generation of sinusoids with frequencies equal to the center frequencies of the bands and amplitudes equal to the rms levels in each band. The sinusoids were summed and presented to listeners for identification. At issue was the number of channels necessary to reach maximum performance on tests of sentence understanding. At +2 dB S/N, the performance maximum was reached with 12 channels of stimulation. At -2 dB S/N, the performance maximum was reached with 20 channels of stimulation. These results, in combination with the outcome that in quiet, asymptotic performance is reached with five channels of stimulation, demonstrate that more channels are needed in noise than in quiet to reach a high level of sentence understanding and that, as the S/N becomes poorer, more channels are needed to achieve a given level of performance.

The identification of speech in noise by cochlear implant patients and normal-hearing listeners using 6-channel signal processors.

OBJECTIVE: To compare the recognition of vowels and sentences in noise by cochlear implant patients using a 6-channel, continuous interleaved sampling (CIS) processor and by normal-hearing subjects listening to speech processed in the manner of the implant processor and output as six amplitude-modulated sine waves. DESIGN: Subjects, 11 normal-hearing listeners and 7 cochlear implant patients, were presented natural vowels produced by men, women, and girls in /hVd/ context and sentences from the Hearing In Noise Test (HINT) lists at +15, +10, and +5 dB signal to noise ratio (SNR) for identification. Stimuli for the normal-hearing subjects were preprocessed through a simulation of a 6-channel implant processor and were output as the sum of sinusoids at the center frequencies of the analysis filters. RESULTS: For the multitalker vowels, four of the seven patients achieved scores within +/-1 standard deviation of the mean for normal-hearing listeners at +15 and +10 dB SNR. At the +5 dB SNR three patients achieved scores within +/-1 standard deviation of the mean for the normal-hearing listeners. For the HINT sentences, four of seven patients achieved scores within +/-1 standard deviation of the mean for the normal-hearing listeners at +15 dB and at +10 dB SNR and two achieved scores within that range at +5 dB SNR. CONCLUSION: Our results extend the range of stimulus conditions, from quiet to modest amounts of noise, in which the CIS strategy allows the best performing patients to extract most, if not all, of the information available to normal-hearing subjects listening to speech processed into six channels.