Objective: Unexplained variability in speech recognition outcomes among postlingually deafened adults with cochlear implants (CIs) is an enormous clinical and research barrier to progress. This variability is only partially explained by patient factors (e.g., duration of deafness) and auditory sensitivity (e.g., spectral and temporal resolution). This study sought to determine whether non-auditory neurocognitive skills could explain speech recognition variability exhibited by adult CI users.
Study Design: Thirty postlingually deafened adults with CIs and thirty age-matched normal-hearing (NH) controls were enrolled.
Methods: Participants were assessed for recognition of words in sentences in noise and several non-auditory measures of neurocognitive function. These non-auditory tasks assessed global intelligence (problem-solving), controlled fluency, working memory, and inhibition-concentration abilities.
Results: For CI users, faster response times during a non-auditory task of inhibition-concentration predicted better recognition of sentences in noise; however, similar effects were not evident for NH listeners.
Conclusions: Findings from this study suggest that inhibition-concentration skills play a role in speech recognition for CI users, but less so for NH listeners. Further research will be required to elucidate this role and its potential as a novel target for intervention.
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http://dx.doi.org/10.1002/lio2.38 | DOI Listing |
JMIR Form Res
January 2025
Faculty of Audiology and Speech Language Pathology, Sri Ramachandra Institute of Higher Education and Research, Chennai, India.
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View Article and Find Full Text PDFAnn N Y Acad Sci
January 2025
Hainan Institute, Zhejiang University, Sanya, China.
In this paper, we introduce FUSION-ANN, a novel artificial neural network (ANN) designed for acoustic emission (AE) signal classification. FUSION-ANN comprises four distinct ANN branches, each housing an independent multilayer perceptron. We extract denoised features of speech recognition such as linear predictive coding, Mel-frequency cepstral coefficient, and gammatone cepstral coefficient to represent AE signals.
View Article and Find Full Text PDFPLoS One
January 2025
College of Computer Science and Technology, Xinjiang University, Urumqi, Xinjiang, China.
In speech signal processing, time-frequency analysis is commonly employed to extract the spectrogram of speech signals. While many algorithms exist to achieve this with high-quality results, they often lack the flexibility to adjust the resolution of the extracted spectrograms. However, applications such as speech recognition and speech separation frequently require spectrograms of varying resolutions.
View Article and Find Full Text PDFCan one shift attention among voices at a cocktail party during a silent pause? Researchers have required participants to attend to one of two simultaneous voices - cued by its gender or location. Switching the target gender or location has resulted in a performance 'switch cost' - which was recently shown to reduce with preparation when a gender cue was presented in advance. The current study asks if preparation for a switch is also effective when a voice is selected by location.
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Department of Otorhinolaryngology, Unidade Local de Saúde de Gaia e Espinho, Gaia, Portugal.
Otosclerosis leads to stapes fixation and consequent conductive hearing loss. Surgery is the mainstay of treatment, and it can be achieved through small fenestra stapedotomy or stapedectomy. Despite the first being favored by most, evidence supporting its superiority over the latter remains inconclusive.
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