Channel vocoders using either tone or band-limited noise carriers have been used in experiments to simulate cochlear implant processing in normal-hearing listeners. Previous results from these experiments have suggested that the two vocoder types produce speech of nearly equal intelligibility in quiet conditions. The purpose of this study was to further compare the performance of tone and noise-band vocoders in both quiet and noisy listening conditions. In each of four experiments, normal-hearing subjects were better able to identify tone-vocoded sentences and vowel-consonant-vowel syllables than noise-vocoded sentences and syllables, both in quiet and in the presence of either speech-spectrum noise or two-talker babble. An analysis of consonant confusions for listening in both quiet and speech-spectrum noise revealed significantly different error patterns that were related to each vocoder's ability to produce tone or noise output that accurately reflected the consonant's manner of articulation. Subject experience was also shown to influence intelligibility. Simulations using a computational model of modulation detection suggest that the noise vocoder's disadvantage is in part due to the intrinsic temporal fluctuations of its carriers, which can interfere with temporal fluctuations that convey speech recognition cues.

Two experiments investigated the impact of reverberation and masking on speech understanding using cochlear implant (CI) simulations. Experiment 1 tested sentence recognition in quiet. Stimuli were processed with reverberation simulation (T=0.425, 0.266, 0.152, and 0.0 s) and then either processed with vocoding (6, 12, or 24 channels) or were subjected to no further processing. Reverberation alone had only a small impact on perception when as few as 12 channels of information were available. However, when the processing was limited to 6 channels, perception was extremely vulnerable to the effects of reverberation. In experiment 2, subjects listened to reverberated sentences, through 6- and 12-channel processors, in the presence of either speech-spectrum noise (SSN) or two-talker babble (TTB) at various target-to-masker ratios. The combined impact of reverberation and masking was profound, although there was no interaction between the two effects. This differs from results obtained in subjects listening to unprocessed speech where interactions between reverberation and masking have been shown to exist. A speech transmission index (STI) analysis indicated a reasonably good prediction of speech recognition performance. Unlike previous investigations, the SSN and TTB maskers produced equivalent results, raising questions about the role of informational masking in CI processed speech.

The Articulation Index (AI) and Speech Intelligibility Index (SII) predict intelligibility scores from measurements of speech and hearing parameters. One component in the prediction is the "importance function," a weighting function that characterizes contributions of particular spectral regions of speech to speech intelligibility. Previous work with SII predictions for hearing-impaired subjects suggests that prediction accuracy might improve if importance functions for individual subjects were available. Unfortunately, previous importance function measurements have required extensive intelligibility testing with groups of subjects, using speech processed by various fixed-bandwidth low-pass and high-pass filters. A more efficient approach appropriate to individual subjects is desired. The purpose of this study was to evaluate the feasibility of measuring importance functions for individual subjects with adaptive-bandwidth filters. In two experiments, ten subjects with normal-hearing listened to vowel-consonant-vowel (VCV) nonsense words processed by low-pass and high-pass filters whose bandwidths were varied adaptively to produce specified performance levels in accordance with the transformed up-down rules of Levitt [(1971). J. Acoust. Soc. Am. 49, 467-477]. Local linear psychometric functions were fit to resulting data and used to generate an importance function for VCV words. Results indicate that the adaptive method is reliable and efficient, and produces importance function data consistent with that of the corresponding AI/SII importance function.

The Articulation Index and Speech Intelligibility Index predict intelligibility scores from measurements of speech and hearing parameters. One component in the prediction is the frequencyimportance function, a weighting function that characterizes contributions of particular spectral regions of speech to speech intelligibility. The purpose of this study was to determine whether such importance functions could similarly characterize contributions of electrode channels in cochlear implant systems. Thirty-eight subjects with normal hearing listened to vowel-consonant-vowel tokens, either as recorded or as output from vocoders that simulated aspects of cochlear implant processing. Importance functions were measured using the method of Whitmal and DeRoy [J. Acoust. Soc. Am. 130, 4032-4043 (2011)], in which signal bandwidths were varied adaptively to produce specified token recognition scores in accordance with the transformed up-down rules of Levitt [J. Acoust. Soc. Am. 49, 467-477 (1971)]. Psychometric functions constructed from recognition scores were subsequently converted into importance functions. Comparisons of the resulting importance functions indicate that vocoder processing causes peak importance regions to shift downward in frequency. This shift is attributed to changes in strategy and capability for detecting voicing in speech, and is consistent with previously measured data.

Two experiments examined the effects of source-to-listener distance ͑SLD͒ on sentence recognition in simulations of cochlear implant usage in noisy, reverberant rooms. Experiment 1 tested sentence recognition for three locations in the reverberant field of a small classroom ͑volume= 79.2 m 3 ͒. Subjects listened to sentences mixed with speech-spectrum noise that were processed with simulated reverberation followed by either vocoding ͑6, 12, or 24 spectral channels͒ or no further processing. Results indicated that changes in SLD within a small room produced only minor changes in recognition performance, a finding likely related to the listener remaining in the reverberant field. Experiment 2 tested sentence recognition for a simulated six-channel implant in a larger classroom ͑volume= 175.9 m 3 ͒ with varying levels of reverberation that could place the three listening locations in either the direct or reverberant field of the room. Results indicated that reducing SLD did improve performance, particularly when direct sound dominated the signal, but did not completely eliminate the effects of reverberation. Scores for both experiments were predicted accurately from speech transmission index values that modeled the effects of SLD, reverberation, and noise in terms of their effects on modulations of the speech envelope. Such models may prove to be a useful predictive tool for evaluating the quality of listening environments for cochlear implant users.