This paper presents the results of a closed-set recognition task for 64 consonant-vowel sounds (16 C X 4 V, spoken by 18 talkers) in speech-weighted noise (-22,-20,-16,-10,-2 [dB]) and in quiet. The confusion matrices were generated using responses of a homogeneous set of ten listeners and the confusions were analyzed using a graphical method. In speech-weighted noise the consonants separate into three sets: a low-scoring set C1 (/f/, /theta/, /v/, /d/, /b/, /m/), a high-scoring set C2 (/t/, /s/, /z/, /S/, /Z/) and set C3 (/n/, /p/, /g/, /k/, /d/) with intermediate scores. The perceptual consonant groups are C1: {/f/-/theta/, /b/-/v/-/d/, /theta/-/d/}, C2: {/s/-/z/, /S/-/Z/}, and C3: /m/-/n/, while the perceptual vowel groups are /a/-/ae/ and /epsilon/-/iota/. The exponential articulation index (AI) model for consonant score works for 12 of the 16 consonants, using a refined expression of the AI. Finally, a comparison with past work shows that white noise masks the consonants more uniformly than speech-weighted noise, and shows that the AI, because it can account for the differences in noise spectra, is a better measure than the wideband signal-to-noise ratio for modeling and comparing the scores with different noise maskers.

The classic [MN55] confusion matrix experiment (16 consonants, white noise masker) was repeated by using computerized procedures, similar to those of Phatak and Allen (2007). ["Consonant and vowel confusions in speech-weighted noise," J. Acoust. Soc. Am. 121, 2312-2316]. The consonant scores in white noise can be categorized in three sets: low-error set [/m/, /n/], average-error set [/p/, /t/, /k/, /s/, /[please see text]/, /d/, /g/, /z/, /Z/], and high-error set /f/theta/b/, /v/, /E/,/theta/]. The consonant confusions match those from MN55, except for the highly asymmetric voicing confusions of fricatives, biased in favor of voiced consonants. Masking noise cannot only reduce the recognition of a consonant, but also perceptually morph it into another consonant. There is a significant and systematic variability in the scores and confusion patterns of different utterances of the same consonant, which can be characterized as (a) confusion heterogeneity, where the competitors in the confusion groups of a consonant vary, and (b) threshold variability, where confusion threshold [i.e., signal-to-noise ratio (SNR) and score at which the confusion group is formed] varies. The average consonant error and errors for most of the individual consonants and consonant sets can be approximated as exponential functions of the articulation index (AI). An AI that is based on the peak-to-rms ratios of speech can explain the SNR differences across experiments.

This paper presents a compact graphical method for comparing the performance of individual hearing impaired ͑HI͒ listeners with that of an average normal hearing ͑NH͒ listener on a consonant-by-consonant basis. This representation, named the consonant loss profile ͑CLP͒, characterizes the effect of a listener's hearing loss on each consonant over a range of performance. The CLP shows that the consonant loss, which is the signal-to-noise ratio ͑SNR͒ difference at equal NH and HI scores, is consonant-dependent and varies with the score. This variation in the consonant loss reveals that hearing loss renders some consonants unintelligible, while it reduces noise-robustness of some other consonants. The conventional SNR-loss metric ⌬SNR 50 , defined as the SNR difference at 50% recognition score, is insufficient to capture this variation. The ⌬SNR 50 value is on average 12 dB lower when measured with sentences using standard clinical procedures than when measured with nonsense syllables. A listener with symmetric hearing loss may not have identical CLPs for both ears. Some consonant confusions by HI listeners are influenced by the high-frequency hearing loss even at a presentation level as high as 85 dB sound pressure level.

Objectives: Over the past decade, U.S. Department of Defense and Veterans Affairs audiologists have reported large numbers of relatively young adult patients who have normal to near-normal audiometric thresholds but who report difficulty understanding speech in noisy environments. Many of these service members also reported having experienced exposure to explosive blasts as part of their military service. Recent studies suggest that some blast-exposed patients with normal to near-normal-hearing thresholds not only have an awareness of increased hearing difficulties, but also poor performance on various auditory tasks (sound source localization, speech recognition in noise, binaural integration, gap detection in noise, etc.). The purpose of this study was to determine the prevalence of functional hearing and communication deficits (FHCD) among healthy Active-Duty service men and women with normal to near-normal audiometric thresholds. Design:To estimate the prevalence of such FHCD in the overall military population, performance of roughly 3400 Active-Duty service members with hearing thresholds mostly within the normal range were measured on 4 hearing tests and a brief 6-question survey to assess FHCD. Subjects were subdivided into 6 groups depending on the severity of the blast exposure (3 levels: none, far away, or close enough to feel heat or pressure) and hearing thresholds (2 levels: audiometric thresholds of 20 dB HL or better, slight elevation in 1 or more thresholds between 500 and 4000 Hz in either ear).Results: While the probability of having hearing difficulty was low (≈4.2%) for the overall population tested, that probability increased by 2 to 3 times if the service member was blast-exposed from a close distance or had slightly elevated hearing thresholds (>20 dB HL). Service members having both blast exposure and mildly elevated hearing thresholds exhibited up to 4 times higher risk for performing abnormally on auditory tasks and more than 5 times higher risk for reporting abnormally low ratings on the subjective questionnaire, compared with service members with no history of blast exposure and audiometric thresholds ≤20 dB HL. Blast-exposed listeners were roughly 2.5 times more likely to experience subjective or objective hearing deficits than those with noblast history.Conclusions: These elevated rates of abnormal performance suggest that roughly 33.6% of Active-Duty service members (or approximately 423,000) with normal to near-normal-hearing thresholds (i.e., H1 profile) are at some risk for FHCD, and about 5.7% (approximately 72,000) are at high risk, but are currently untested and undetected within the current fitness-for-duty standards. Service members identified as "at risk" for FHCD according to the metrics used in the present study, in spite of their excellent hearing thresholds, require further testing to determine whether they have sustained damage to peripheral and early-stage auditory processing (bottom-up processing), damage to cognitive processes for speech (top-down processing), or bo...

This study measured the influence of masker fluctuations on phoneme recognition. The first part of the study compared the benefit of masker modulations for consonant and vowel recognition in normal-hearing (NH) listeners. Recognition scores were measured in steady-state and sinusoidally amplitude-modulated noise maskers (100% modulation depth) at several modulation rates and signal-to-noise ratios. Masker modulation rates were 4, 8, 16, and 32 Hz for the consonant recognition task and 2, 4, 12, and 32 Hz for the vowel recognition task. Vowel recognition scores showed more modulation benefit and a more pronounced effect of masker modulation rate than consonant scores. The modulation benefit for word recognition from other studies was found to be more similar to the benefit for vowel recognition than that for consonant recognition. The second part of the study measured the effect of modulation rate on the benefit of masker modulations for vowel recognition in aided hearing-impaired (HI) listeners. HI listeners achieved as much modulation benefit as NH listeners for slower masker modulation rates (2, 4, and 12 Hz), but showed a reduced benefit for the fast masker modulation rate of 32 Hz.