Background and Aim: It will be discussed about five mechanisms in relation to SPEECH in NOISE PERCEPTION; including neural encoding and decoding, centrifugal pathways, pitch percep-tion, asymmetric sampling in time and cognitive skills. These mechanisms are related to each other and each is important to recognize SPEECH in NOISE. In this article, we have tried to rely on the latest studies to describe the mechanisms as mentioned. In the end, we will refer to word in NOISE training.Methods: In this review study, the articles rela-ted to SPEECH PERCEPTION in NOISE published in Google Scholar, PubMed, Scopus and Springer database, were collected and investigated. Key-words include SPEECH in NOISE and related words.Conclusion: It can be concluded that mentioned mechanisms have a considerable effect on spee-ch in NOISE PERCEPTION. It should be noticed that word in NOISE training cause these mechanisms to improve by covering some of them.

Background and Aim: In most everyday sett-ings, SPEECH is heard in the presence of com-peting sounds and SPEECH PERCEPTION in NOISE is affected by various factors, including cognitive factors. In this regard, bilingualism is a pheno-menon that changes cognitive and behavioral processes as well as the nervous system. This study aimed to evaluate SPEECH PERCEPTION in NOISE and compare differences in Kurd-Persian bilinguals versus Persian monolinguals. Methods: This descriptive-analytic study was performed on 92 students with normal hearing, 46 of whom were bilingual Kurd-Persian with a mean (SD) age of 22. 73 (1. 92) years, and 46 other Persian monolinguals with a mean (SD) age of 22. 71 (2. 28) years. They were examined by consonant-vowel in NOISE (CV in NOISE) test and quick SPEECH in NOISE (Q-SIN) test. The obtained data were analyzed by SPSS 21. Results: The comparison of the results showed differences in both tests between bilingual and monolingual subjects. In both groups, the reduc-tion of signal-to-NOISE ratio led to lower scores, but decrease in CV in NOISE test in bilinguals was less than monolinguals (p < 0. 001) and in the Q-SIN test, the drop in bilinguals’ score was more than monolinguals (p = 0. 002). Conclusion: Kurd-Persian bilinguals had a bet-ter performance in CV in NOISE test but had a worse performance in Q-SIN test than Persian monolinguals.

Background and Aim: SPEECH-in-NOISE (SIN) PERCEPTION is one of the most important issues processed by human listeners. The purpose of SPEECH tests is to determine the perceptual abilities of people in real life conditions,therefore, can SPEECH tests in quiet be a valuable measure of this ability? Is the central representation of SPEECH-in-quiet and SIN PERCEPTION the same? This review study aimed to investigate the central representation of SIN PERCEPTION in healthy individuals aged 14 to 60 years. Recent Findings: Central representation of SIN PERCEPTION is influenced by various peripheral factors and includes several neural processes. All auditory nerve fibers are stimulated by SPEECH and NOISE. Low-frequency sounds play a much more important role than high-frequencies. The auditory nerve fibers that are stimulated by SPEECH, respond only to fundamental frequencies (F0). The degree of neural synchronization that increases by NOISE and causes the simultaneous activity of these fibers, develops auditory processing. Large areas of the auditory cortex and its external parts (parietal, premotor, and mirror neurons) are stimulated. Larger groups of cortical nerve fibers are used for SPEECH signals of the same family with significant ecological importance. Conclusion: Central representation of SIN PERCEPTION is not the same as in quiet. SPEECH PERCEPTION tests in quiet cannot assess real-life perceptual abilities of people. SIN tests should be used routinely as a practical confirmatory test in audiology clinics. It is very necessary that the list of words and sentences required for SIN PERCEPTION tests be prepared for different languages.

In traditional SPEECH processing, feature extraction and classification were conducted as separate steps. The advent of deep neural networks has enabled methods that simultaneously model the relationship between acoustic and phonetic characteristics of SPEECH while classifying it directly from the raw waveform. The first convolutional layer in these networks acts as a filter bank. To enhance interpretability and reduce the number of parameters, researchers have explored the use of parametric filters, with the SincNet architecture being a notable advancement. In SincNet's initial convolutional layer, rectangular bandpass filters are learned instead of fully trainable filters. This approach allows for modeling with fewer parameters, thereby improving the network's convergence speed and accuracy. Analyzing the learned filter bank also provides valuable insights into the model's performance. The reduction in parameters, along with increased accuracy and interpretability, has led to the adoption of various parametric filters and deep architectures across diverse SPEECH processing applications. This paper introduces different types of parametric filters and discusses their integration into various deep architectures. Additionally, it examines the specific applications in SPEECH processing where these filters have proven effective.

Objectives: Studies have shown that spatial processing disorders can be the reason for hearing impairment in the elderly but none of the auditory training programs has addressed it. This study investigated the effect of a novel auditory training on SPEECH PERCEPTION in NOISE among the elderly and its maintenance. Materials and Methods: The spatial versions of the Persian quick SPEECH in NOISE (QuickSIN) test were developed and its face validity and reliability were evaluated. Thirty-six old subjects with normal hearing ability who expressed problem in SPEECH PERCEPTION were randomly divided into the study and control groups. The study group received 5 weeks of spatial auditory training. The spatial versions of the QuickSIN test, and Iranian version of the SPEECH, spatial, and qualities of hearing scale (SSQ), as well as the middle latency response (MLR) test were done pre and post training. The same evaluations were carried out for the control group without training. Results: Test-retest reliability and face validity of the spatial versions of Persian QuickSIN test were confirmed. Signal to NOISE ratio for 50% correct score (SNR50) significantly decreased and spatial release from masking (SRM) and binaural interaction component of MLR percentage (BIC-MLR%) significantly increased. The average scores of SSQ improved in all the three domains. These changes, except for BIC-MLR and SNR50a had short-term maintenance. Conclusions: Spatial auditory training can improve SPEECH PERCEPTION in NOISE by enhancing the representation of binaural cues at the thalamocortical level. Spatial hearing evaluation and training are recommended to be incorporated into audiology services for serving the geriatric population.

Background and Aim: Despite more affordable and advanced technologies for early detection of congenital hearing loss, unilateral hearing loss is the prevalent form of hearing loss affecting school-aged children. This study aimed to examine the impact of Words-in-NOISE (WIN) training on SPEECH PERCEPTION of NOISE in children with unilateral hearing loss. Methods: Thirteen children aged 8 to 12 years with unilateral hearing loss underwent a WIN training program in NOISE. The participants were tested before and after training on word identification in NOISE and cortical auditory evoked potentials. Results: A comparison of the mean signal-to-NOISE ratio 50% between pre-and post-training indicated that signal-to-NOISE ratio 50% score decreased after training sessions. WIN training reduced the latency in N1 and P2 waves in the Fz electrode and the N1 wave in the Pz electrode and increased the amplitude of the waves in the Fz and Pz electrodes. The observed data suggest that all participants’,performance improved on word identification in NOISE and some electrophysiological parameters. Cortical auditory evoked potentials components changes did not correlate with the WIN scores. Conclusion: The Persian version of the WIN training improved SPEECH PERCEPTION ability in the presence of competitive NOISE in children with unilateral hearing loss. Therefore, this software solution can partially solve SPEECH comprehension problems with NOISE in these children.

Background and Aim: The output Signal-to-NOISE Ratio (SNR) is one of the essential factors in hearing aid benefits. There is limited evidence regarding SNR improvement by the Channel-Free (CFHA) and Multi-Channel Hearing Aid (MCHA) and the SPEECH understanding in NOISE through them. This study aimed to investigate the extent to which output SNR was modified by CFHA and MCHA processing and the variation in aided SPEECH recognition abilities with a change in output SNR. Methods: Thirty-six participants aged 50–65 years were included. A chosen CFHA and MCHA were used to obtain the output SNR and sentence recognition in NOISE in four different processing algorithms (linear, linear+NOISE reduction, WDRC, WDRC+NOISE reduction). Hagerman’s phase inversion technique was used to measure the attenuation of NOISE and, in turn, to obtain the output SNR of the hearing aid. Results: In all hearing aid processing algorithms among those with normal hearing and people with hearing loss, the output of CFHA revealed higher attenuation values than that of MCHA. There was a significant effect of the hearing aids and processing algorithms in both normal and individuals with hearing impairment on the mean SNR. Further, multiple linear regression analysis results showed that whether the hearing is channel-free or multichannel significantly predicted SPEECH recognition scores, while output SNR and processing algorithms did not. Conclusion: The signal processing algorithms in CFHA had greater NOISE attenuation values, better output SNR, and SPEECH recognition scores, showing an advantage over the modern MCHA among individuals with hearing impairment.