Spectral and temporal cues for phoneme recognition in noise

Electrical field interaction caused by current spread in a cochlear implant was modeled in an explicit way in an acoustic model (the SPREAD model) presented to six listeners with normal hearing. The typical processing of cochlear implants was modeled more closely than in traditional acoustic models by careful selection of parameters related to current spread or parameters that could amplify the electrical field interactions caused by current spread. These parameters were the insertion depth, electrode spacing, electrical dynamic range, and dynamic range compression function. The hypothesis was that current spread could account for the asymptote in performance in speech intelligibility experiments observed at around seven stimulation channels in a number of cochlear implant studies. Speech intelligibility for sentences, vowels, and consonants at three noise levels (SNR of +15 dB, +10 dB, and +5 dB) was measured as a function of the number of spectral channels (4, 7, and 16). The SPREAD model appears to explain the asymptote in speech intelligibility at seven channels for all noise levels for all speech material used in this study. It is shown that the compressive amplitude mapping used in cochlear implants can have a detrimental effect on the number of effective channels.

Section: Consonant Intelligibilitysupporting

confidence: 47%

An analysis of the effects of electrical field interaction with an acoustic model of cochlear implants

Strydom

Hanekom

2011

“…Many studies in the literature have suggested that speech recognition in noise is dependent on spectral resolution to a greater degree than speech recognition in quiet. Vocoder studies have suggested that a substantially increased number of channels is needed for listening in noise backgrounds (Dorman et al, 1998;Xu and Zheng, 2007), particularly for vowel and voice pitch perception (approximately > 20 channels) (Kong and Zeng, 2006). The effective number of channels in a cochlear implant has found to be much lower (i.e., $8) than the number of implanted electrodes (Friesen et al, 2001).…”

Section: B Effects Of Neural Survival On Speech Recognition In Noisementioning

confidence: 99%

Relationship between multipulse integration and speech recognition with cochlear implants

Zhou

Pfingst

2014

Comparisons of performance with cochlear implants and postmortem conditions in the cochlea in humans have shown mixed results. The limitations in those studies favor the use of within-subject designs and non-invasive measures to estimate cochlear conditions. One non-invasive correlate of cochlear health is multipulse integration, established in an animal model. The present study used this measure to relate neural health in human cochlear implant users to their speech recognition performance. The multipulse-integration slopes were derived based on psychophysical detection thresholds measured for two pulse rates (80 and 640 pulses per second). A within-subject design was used in eight subjects with bilateral implants where the direction and magnitude of ear differences in the multipulse-integration slopes were compared with those of the speech-recognition results. The speech measures included speech reception threshold for sentences and phoneme recognition in noise. The magnitude of ear difference in the integration slopes was significantly correlated with the magnitude of ear difference in speech reception thresholds, consonant recognition in noise, and transmission of place of articulation of consonants. These results suggest that multipulse integration predicts speech recognition in noise and perception of features that use dynamic spectral cues.

“…Temporal envelope modulations suffice to provide intelligible speech for as few as four spectral channels under ideal conditions ͑Shannon et al., 1995;Dorman et al, 1997͒. However, when the channels' envelope modulations are low-pass filtered with cutoff frequencies in the 8-16 Hz range, intelligibility decreases ͑Fu and Shannon, 2000;Xu and Zheng, 2007͒. Reverberation, which can act as a low-pass filter for envelope modulations in this frequency range ͑Houtgast and Steeneken, 1985͒, has similarly been shown to degrade intelligibility for listening through actual or simulated implants in rooms that listeners with normal hearing would find acceptable ͑Iglehart, 2004; Poissant et al, 2006͒. Studies of intelligibility for implant users in reverberant spaces have typically focused on the use of frequency modulation ͑FM͒ or sound field devices to improve intelligibility ͑Crandell et Iglehart, 2004;Anderson et al, 2005͒, with mixed results.…”

Section: Introductionmentioning

confidence: 99%

Effects of source-to-listener distance and masking on perception of cochlear implant processed speech in reverberant rooms

Whitmal

Poissant

2009

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.