Speech recognition in noise as a function of the number of spectral channels: Comparison of acoustic hearing and cochlear implants

Abstract

Speech recognition was measured as a function of spectral resolution (number of spectral channels) and speech-to-noise ratio in normal-hearing (NH) and cochlear-implant (CI) listeners. Vowel, consonant, word, and sentence recognition were measured in five normal-hearing listeners, ten listeners with the Nucleus-22 cochlear implant, and nine listeners with the Advanced Bionics Clarion cochlear implant. Recognition was measured as a function of the number of spectral channels (noise bands or electrodes) at signal-to-noise ratios of + 15, + 10, +5, 0 dB, and in quiet. Performance with three different speech processing strategies (SPEAK, CIS, and SAS) was similar across all conditions, and improved as the number of electrodes increased (up to seven or eight) for all conditions. For all noise levels, vowel and consonant recognition with the SPEAK speech processor did not improve with more than seven electrodes, while for normal-hearing listeners, performance continued to increase up to at least 20 channels. Speech recognition on more difficult speech materials (word and sentence recognition) showed a marginally significant increase in Nucleus-22 listeners from seven to ten electrodes. The average implant score on all processing strategies was poorer than scores of NH listeners with similar processing. However, the best CI scores were similar to the normal-hearing scores for that condition (up to seven channels). CI listeners with the highest performance level increased in performance as the number of electrodes increased up to seven, while CI listeners with low levels of speech recognition did not increase in performance as the number of electrodes was increased beyond four. These results quantify the effect of number of spectral channels on speech recognition in noise and demonstrate that most CI subjects are not able to fully utilize the spectral information provided by the number of electrodes used in their implant.

A comparison of the speech recognition and pitch ranking abilities of children using a unilateral cochlear implant, bimodal stimulation or bilateral hearing aids

“…Spearman's rho (ρ) nonparametric correlations were used to investigate potential relationships between test scores and variables known to impact on the performance of such tasks including chronological age [43,44,45], duration of listening device usage [46,47], better ear PTA [48,49], and musical experience level (MEL) [29]. For these correlations summary scores were calculated for each hearing-impaired participant including: mean CNC words correct; mean HINT sentences in quiet correct; mean HINT sentences in noise correct (average score for the S0N0, S0NCI and S0NHA conditions); and mean PRT accuracy (average PRT score across all sessions and subtests).…”

“…Overlapping electrical currents occur because intracochlear electrode arrays are surrounded by highly conductive fluid that fills scala tympani [2]. Current evidence suggests only 4 to 8 independent sites of stimulation are available, even for arrays with 22 electrodes [44,45]. A host of biological variables can also limit the ability of CI users to use place cues including the density, and distribution of spiral ganglion neurons relative to electrode array and/or the pathophysiology of the hearing los [46,47].…”

Use of Amplitude Modulation Cues Recovered from Frequency Modulation for Cochlear Implant Users When Original Speech Cues Are Severely Degraded

“…With this design, robust speech identification in quiet is possible with four to six frequency channels (Dorman et al 1989;Fishman et al 1997;Friesen et al 2001). However, a serious limitation of this design is that AM cues are highly susceptible to noise.…”

“…However, a serious limitation of this design is that AM cues are highly susceptible to noise. This imposes a rapid deterioration in speech identification performance with increasing levels of background noise (Fu et al 1998;Friesen et al 2001;Fu and Nogaki 2005). An alternative method of delivering speech information is the use of frequency modulation (FM), often referred to as "acoustic temporal fine structure" (Qin and Oxenham 2003;Zeng et al 2005;Drennan et al 2008).…”

“…These five potential sources of distortion were chosen for the present study because they are known to affect the transmission of modulation cues that are crucial for speech understanding for CI users [e.g., background noise, Fu and Nogaki (2005); reverberation, amplitude compression, Zeng (2004);IDR, Spahr et al (2007); number of channels, Friesen et al (2001]. In addition, multiple levels of distortion were tested for each of these five sources of distortion.…”