This measure represents the percentage of identified as having deaf & hard of hearing impairments who were competitively employed after receiving services from Iowa Vocational Rehabilitation Services.

"BACKGROUND: This study aimed to evaluate the association of chronic rhinosinusitis with sudden sensorineural hearing loss using a population-based database. METHODS: Sampled subject data were obtained from the Taiwan Longitudinal Health Insurance Database 2000. A total of 3325 patients with sudden sensorineural hearing loss were identified and 9975 controls were randomly selected. A conditional logistic regression was used to calculate the odds ratio for having been previously diagnosed with chronic rhinosinusitis, for cases and controls. RESULTS AND CONCLUSION: The adjusted odds ratio of having prior chronic rhinosinusitis among cases compared to controls was 1.36 (95 per cent confidence interval = 1.16-1.60). The significant relationship between sudden sensorineural hearing loss and chronic rhinosinusitis was most pronounced among those patients aged 44 years or less (compared to controls) (odds ratio = 2.18； 95 per cent confidence interval = 1.63-2.92). However, the significant relationship between sudden sensorineural hearing loss and prior chronic rhinosinusitis was not sustained for patients older than 60 years compared to controls."

Purpose: The classroom acoustic standard ANSI/ASA S12.60-2010/Part 1 requires a reverberation time (RT) for children with hearing impairment of 0.3 s, shorter than its requirement of 0.6 s for children with typical hearing. While preliminary data from conference proceedings support this new RT requirement of 0.3 s, peer-reviewed data that support 0.3-s RT are not available on those wearing hearing aids. To help address this, this article compares speech perception performance by children with hearing aids in RTs, including those specified in the ANSI/ASA-2010 standard. A related clinical issue is whether assessments of speech perception conducted in near-anechoic sound booths, which may overestimate performance in reverberant classrooms, may now provide a more reliable estimate when the child is in a classroom with a short RT of 0.3 s. To address this, this study compared speech perception by children with hearing aids in a sound booth to listening in 0.3-s RT.Method: Participants listened in classroom RTs of 0.3, 0.6, and 0.9 s and in a near-anechoic sound booth. All conditions also included a 21-dB range of speech-to-noise ratios (SNRs) to further represent classroom listening environments. Performance measures using the Bamford–Kowal–Bench Speech-in-Noise (BKB-SIN) test were 50% correct word recognition across these acoustic conditions, with supplementary analyses of percent correct. Results: Each reduction in RT from 0.9 to 0.6 to 0.3 s significantly benefited the children’s perception of speech. Scores obtained in a sound booth were significantly better than those measured in 0.3-s RT.Conclusion: These results support the acoustic standard of 0.3-s RT for children with hearing impairment in learning spaces ≤ 283 m3, as specified in ANSI/ASA S12.60-2010/Part 1. Additionally, speech perception testing in a sound booth did not predict accurately listening ability in a classroom with 0.3-s RT.Supplemental Material S1. Reverberation times for each classroom condition.Supplemental Material S2. Speech perception scores (% correct) for each listening condition.Iglehart, F. (2019). Speech perception in classroom acoustics by children with hearing loss and wearing hearing aids. American Journal of Audiology. Advance online publication. https://doi.org/10.1044/2019_AJA-19-0010

Database and data set of known mutations in connexins related to deafness with associated information including published work and classification scheme. Users may submit new mutations. A large number of subjects are affected by hearing impairment. In developed countries deafness has an important genetic origin and at least 60% of the cases are inherited. The pattern of inheritance can be dominant, recessive, X-linked and mitochondrial. Many genes are involved in the different types of deafness (syndromic and non-syndromic). Non-syndromic hereditary deafness is mainly (80%) due to recessive genes (or mutations). It is believed that more than one hundred genes could be involved in hearing impairment. Several of these genes have been identified recently by positional cloning or positional candidate gene approaches. Despite the fact that more than 20 loci have been described for non-syndromic autosomal recessive deafness (DFNB), a single locus, DFNB1, accounts for a high proportion of the cases, with variability depending on the population. The gene involved in this type of deafness is GJB2, which encodes the gap junction protein connexin 26(Cx26). NEW Recent data indicates that DFNB1 can also be due to a deletion of 342Kb involving GJB6, a gene that is very close to GJB2. This deletion has been reported to cause deafness both in the homozygous status and in heterozygosity with a GJB2 point mutation in trans (see big deletions affecting connexin genes...). Connexins are transmembrane proteins that form channels allowing rapid transport of ions or small molecules between cells. There are two types of connexins, alpha and beta, named GJA or GJB followed by a number. Connexins are expressed in many different tissues. Other connexin genes are also involved in deafness. These are GJB1 (Cx32), which is also responsible for X-linked Charcot-Marie-Tooth disease type I; GJB3 (Cx31), involved in both deafness or a skin disease, erythrokeratodermia variabilis, depending on the location of the mutation; GJB6 (Cx30), which has been related to a dominant type of deafness in an Italian family and NEW GJA1 (Cx43), which has recently been shown to be involved in recessive deafness.

Emotion expression is an essential part of human interaction. The same text can hold different meanings when expressed with different emotions. Thus understanding the text alone is not enough for getting the meaning of an utterance. Acted and natural corpora have been used to detect emotions from speech. Many speech databases for different languages including English, German, Chinese, Japanese, Russian, Italian, Swedish and Spanish exist for modeling emotion recognition. Since there is no reported reference of an available Arabic corpus, we decided to collect the first Arabic Natural Audio Dataset (ANAD) to recognize discrete emotions.

Embedding an effective emotion detection feature in speech recognition system seems a promising solution for decreasing the obstacles faced by the deaf when communicating with the outside world. There exist several applications that allow the deaf to make and receive phone calls normally, as the hearing-impaired individual can type a message and the person on the other side hears the words spoken, and as they speak, the words are received as text by the deaf individual. However, missing the emotion part still makes these systems not hundred percent reliable. Having an effective speech to text and text to speech system installed in their everyday life starting from a very young age will hopefully replace the human ear. Such systems will aid deaf people to enroll in normal schools at very young age and will help them to adapt better in classrooms and with their classmates. It will help them experience a normal childhood and hence grow up to be able to integrate within the society without external help.

Eight videos of live calls between an anchor and a human outside the studio were downloaded from online Arabic talk shows. Each video was then divided into turns: callers and receivers. To label each video, 18 listeners were asked to listen to each video and select whether they perceive a happy, angry or surprised emotion. Silence, laughs and noisy chunks were removed. Every chunk was then automatically divided into 1 sec speech units forming our final corpus composed of 1384 records.

Twenty five acoustic features, also known as low-level descriptors, were extracted. These features are: intensity, zero crossing rates, MFCC 1-12 (Mel-frequency cepstral coefficients), F0 (Fundamental frequency) and F0 envelope, probability of voicing and, LSP frequency 0-7. On every feature nineteen statistical functions were applied. The functions are: maximum, minimum, range, absolute position of maximum, absolute position of minimum, arithmetic of mean, Linear Regression1, Linear Regression2, Linear RegressionA, Linear RegressionQ, standard Deviation, kurtosis, skewness, quartiles 1, 2, 3 and, inter-quartile ranges 1-2, 2-3, 1-3. The delta coefficient for every LLD is also computed as an estimate of the first derivative hence leading to a total of 950 features.

I would have never reached that far without the help of my supervisors. I warmly thank and appreciate Dr. Rached Zantout, Dr. Lama Hamandi, and Dr. Ziad Osman for their guidance, support and constant supervision.

IntroductionCandidacy criteria for cochlear implantation in the United States has expanded to include children with single-sided deafness (SSD) who are at least 5 years of age. Pediatric cochlear implant (CI) users with SSD experience improved speech recognition with increased daily device use. There are few studies that report the hearing hour percentage (HHP) or the incidence of non-use for pediatric CI recipients with SSD. The aim of this study was to investigate factors that impact outcomes in children with SSD who use CIs. A secondary aim was to identify factors that impact daily device use in this population.MethodsA clinical database query revealed 97 pediatric CI recipients with SSD who underwent implantation between 2014 and 2022 and had records of datalogs. The clinical test battery included speech recognition assessment for CNC words with the CI-alone and BKB-SIN with the CI plus the normal-hearing ear (combined condition). The target and masker for the BKB-SIN were presented in collocated and spatially separated conditions to evaluate spatial release from masking (SRM). Linear mixed-effects models evaluated the influence of time since activation, duration of deafness, HHP, and age at activation on performance (CNC and SRM). A separate linear mixed-effects model evaluated the main effects of age at testing, time since activation, duration of deafness, and onset of deafness (stable, progressive, or sudden) on HHP.ResultsLonger time since activation, shorter duration of deafness, and higher HHP were significantly correlated with better CNC word scores. Younger age at device activation was not found to be a significant predictor of CNC outcomes. There was a significant relationship between HHP and SRM, with children who had higher HHP experiencing greater SRM. There was a significant negative correlation between time since activation and age at test with HHP. Children with sudden hearing loss had a higher HHP than children with progressive and congenital hearing losses.ConclusionThe present data presented here do not support a cut-off age or duration of deafness for pediatric cochlear implantation in cases of SSD. Instead, they expand on our understanding of the benefits of CI use in this population by reviewing the factors that influence outcomes in this growing patient population. Higher HHP, or greater percentage of time spent each day using bilateral input, was associated with better outcomes in the CI-alone and in the combined condition. Younger children and those within the first months of use had higher HHP. Clinicians should discuss these factors and how they may influence CI outcomes with potential candidates with SSD and their families. Ongoing work is investigating the long-term outcomes in this patient population, including whether increasing HHP after a period of limited CI use results in improved outcomes.

Hearing loss (HL) is the most common sensory deficit in humans and is frequently accompanied by peripheral vestibular loss (PVL). While often overlooked, PVL is an important sensory dysfunction that may impair development of motor milestones in children and can have a significant negative impact on quality of life. In addition, many animal and in vitro models of deafness use vestibular hair cells as a proxy to study cochlear hair cells. The extent of vestibular end organ dysfunction associated with genetic pediatric hearing loss is not well-understood. We studied children with a known genetic cause of hearing loss who underwent routine preoperative vestibular testing prior to cochlear implantation between June 2014 and July 2020. Vestibular testing included videonystagmography, rotary chair, video head impulse testing, and/or vestibular evoked myogenic potentials. Etiology of HL was determined through history, physical examination, imaging, laboratory testing, and/or genetic testing. Forty-four children (21 female/23 male) met inclusion criteria; 24 had genetic non-syndromic and 20 had genetic syndromic forms of HL. Mean age at the time of testing was 2.8 ± 3.8 years (range 7 months−17 years). The most common cause of non-syndromic HL was due to mutations in GJB2 (n = 13) followed by MYO15A (3), MYO6 (2), POU3F4 (2), TMPRSS3 (1), CDH23 (1), TMC1 (1), and ESRRB (1). The most common forms of syndromic HL were Usher syndrome (4) and Waardenburg (4), followed by SCID/reticular dysgenesis (3), CHARGE (2), CAPOS (1), Coffin-Siris (1), Jervell and Lange-Nielsen (1), Noonan (1), peroxisome biogenesis disorder (1), Perrault (1), and Trisomy 21 (1). Overall, 23 patients (52%) had PVL. A larger proportion of children with syndromic forms of HL had PVL (12/20, 60%) compared with children with genetic non-syndromic HL (11/24, 46%), though without statistical significant (p = 0.3). The occurrence of PVL varied by affected gene. In conclusion, PVL is a common finding in children with syndromic and non-syndromic genetic HL undergoing vestibular evaluation prior to cochlear implantation. Improved understanding of the molecular physiology of vestibular hair cell dysfunction is important for clinical care as well as research involving vestibular hair cells in model organisms and in vitro models.

Hearing loss is a problem that impacts a significant proportion of the adult population. Cochlear hair cell (HC) loss due to loud noise, chemotherapy and aging is the major underlying cause. A significant proportion of these individuals are dissatisfied with available treatment options which include hearing aids and cochlear implants. An alternative approach to restore hearing would be to regenerate HCs. Such therapy would require a recapitulation of the complex architecture of the organ of Corti, necessitating regeneration of both mature HCs and supporting cells (SCs). Transcriptional profiles of the mature cell types in the cochlea are necessary to can provide a metric for eventual regeneration therapies. To assist in this effort, we sought to provide the first single-cell characterization of the adult cochlear SC transcriptome. We performed single-cell RNA-Seq on FACS-purified adult cochlear SCs from the LfngEGFP adult mouse, in which SCs express GFP. We demonstrate that adult cochlear SCs are transcriptionally distinct from their perinatal counterparts. We establish cell-type-specific adult cochlear SC transcriptome profiles, and we validate these expression profiles through a combination of both fluorescent immunohistochemistry and in situ hybridization co-localization and quantitative polymerase chain reaction (qPCR) of adult cochlear SCs. Furthermore, we demonstrate the relevance of these profiles to the adult human cochlea through immunofluorescent human temporal bone histopathology. Finally, we demonstrate cell cycle regulator expression in adult SCs and perform pathway analyses to identify potential mechanisms for facilitating mitotic regeneration (cell proliferation, differentiation, and eventually regeneration) in the adult mammalian cochlea. Our findings demonstrate the importance of characterizing mature as opposed to perinatal SCs.

Incidence of patients with hearing loss, 2011–2020 (per 100,000).