Sound Classification Based on Modified Log Energy for Digital Hearing Aids

2012 ◽  
Author(s):  
Xiaoli Han ◽  
Ling Xiao ◽  
Jie Cui
Keyword(s):  
Hearing Aids ◽  
Digital Hearing Aids ◽  
Sound Classification

scholarly journals A method for enhancing speech and warning signals based on parallel convolutional neural networks in a noisy environment

2021 ◽  
Vol 29 ◽  
pp. 141-152
Author(s):  
Ha Lim Kang ◽  
Sung Dae Na ◽  
Myoung Nam Kim
Keyword(s):  
Neural Networks ◽  
Hearing Loss ◽  
Hearing Aids ◽  
Noisy Environment ◽  
Warning Signals ◽  
Digital Hearing Aids ◽  
Sound Classification ◽  
Frequency Domains ◽  
Convolution Filter ◽  
Deep Learning Model

BACKGROUND: Digital hearing aids are based on technology that amplifies sound and removes noise according to the frequency of hearing loss in hearing loss patients. However, within the noise removed is a warning sound that alert the listener; the listener may be exposed to danger because the warning sound is not recognized. OBJECTIVE: In this paper, a deep learning model was used to improve these limits and propose a method to distinguish the warning sound in speech signals mixed with noise. In addition, the improved speech and warning sound were derived by removing noise present in the classification sound signals. METHODS: To classify the sound dataset, an adaptive convolution filter that changes according to two signals is proposed. The proposed convolution filter is applied to the PCNNs model to analyze the characteristics of the time and frequency domains of the dataset and classify the presence or absence of warning sound. In addition, the CEDN model was used to improve the intelligibility of the warning and the speech in the signal based on the warning sound classification from the proposed PCNNs model. RESULTS: Experimental results show that the PCNNs model using the proposed multiplicative filters is efficient for analyzing sound signals with complex frequencies. In addition, the CEDN model was used to improve the intelligibility of the warning and the speech in the signal based on the warning sound classification from the proposed PCNNs model. CONVLUSION: We confirmed that the PCNN model with the proposed filter showed the highest training rate, lowest error rate, and the most stable results. In addition, the CEDN model confirmed that speech and warning sounds were recognized, but it was confirmed that there was a limitation in clearly recognizing speech as the noise ratio increased.

Performance Improvement of Digital Hearing Aid Systems

2015 ◽  
Vol 1 ◽  
pp. 27
Author(s):  
Isiaka Ajewale Alimi
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Digital Signal Processor ◽  
Speech Intelligibility ◽  
Communication Systems ◽  
Hearing Aid ◽  
Spectral Subtraction ◽  
Residual Spectrum ◽  
Digital Hearing Aids ◽  
Digital Hearing Aid

Digital hearing aids addresses the issues of noise and speech intelligibility that is associated with the analogue types. One of the main functions of the digital signal processor (DSP) of digital hearing aid systems is noise reduction which can be achieved by speech enhancement algorithms which in turn improve system performance and flexibility. However, studies have shown that the quality of experience (QoE) with some of the current hearing aids is not up to expectation in a noisy environment due to interfering sound, background noise and reverberation. It is also suggested that noise reduction features of the DSP can be further improved accordingly. Recently, we proposed an adaptive spectral subtraction algorithm to enhance the performance of communication systems and address the issue of associated musical noise generated by the conventional spectral subtraction algorithm. The effectiveness of the algorithm has been confirmed by different objective and subjective evaluations. In this study, an adaptive spectral subtraction algorithm is implemented using the noise-estimation algorithm for highly non-stationary noisy environments instead of the voice activity detection (VAD) employed in our previous work due to its effectiveness. Also, signal to residual spectrum ratio (SR) is implemented in order to control the amplification distortion for speech intelligibility improvement. The results show that the proposed scheme gives comparatively better performance and can be easily employed in digital hearing aid system for improving speech quality and intelligibility.

Expectations, Prefitting Counseling, and Hearing Aid Outcome

2009 ◽  
Vol 20 (05) ◽  
pp. 320-334 ◽  
Author(s):  
Gabrielle H. Saunders ◽  
M Samantha Lewis ◽  
Anna Forsline
Keyword(s):  
Hearing Aids ◽  
Hearing Aid ◽  
Well Being ◽  
Fine Tuning ◽  
Initial Contact ◽  
High Expectations ◽  
Digital Hearing Aids ◽  
The Impact ◽  
Unrealistic Expectations

Background: Data suggest that having high expectations about hearing aids results in better overall outcome. However, some have postulated that excessively high expectations will result in disappointment and thus poor outcome. It has been suggested that counseling patients with unrealistic expectations about hearing aids prior to fitting may be beneficial. Data, however, are mixed as to the effectiveness of such counseling, in terms of both changes in expectations and final outcome. Purpose: The primary purpose of this study was to determine whether supplementing prefitting counseling with demonstration of real-world listening can (1) alter expectations of new hearing aid users and (2) increase satisfaction over verbal-only counseling. Secondary goals of the study were to examine (1) the relationship between prefitting expectations and postfitting outcome, and (2) the effect of hearing aid fine-tuning on hearing aid outcome. Research Design: Sixty new hearing aid users were fitted binaurally with Beltone Oria behind-the-ear digital hearing aids. Forty participants received prefitting counseling and demonstration of listening situations with the Beltone AVE™ (Audio Verification Environment) system; 20 received prefitting counseling without a demonstration of listening situations. Hearing aid expectations were measured at initial contact and following prefitting counseling. Reported hearing aid outcome was measured after eight to ten weeks of hearing aid use. Study Sample: Sixty new hearing aid users aged between 55 and 81 years with symmetrical sensorineural hearing loss. Intervention: Participants were randomly assigned to one of three experimental groups, between which the prefitting counseling and follow-up differed: Group 1 received prefitting counseling in combination with demonstration of listening situations. Additionally, if the participant had complaints about sound quality at the follow-up visit, the hearing aids were fine-tuned using the Beltone AVE system. Group 2 received prefitting counseling in combination with demonstration of listening situations with the Beltone AVE system, but no fine-tuning was provided at follow-up. Group 3 received prefitting hearing aid counseling that did not include demonstration of listening, and the hearing aids were not fine-tuned at the follow-up appointment. Results: The results showed that prefitting hearing aid counseling had small but significant effects on expectations. The two forms of counseling did not differ in their effectiveness at changing expectations; however, anecdotally, we learned from many participants that that they enjoyed listening to the auditory demonstrations and that they found them to be an interesting listening exercise. The data also show that positive expectations result in more positive outcome and that hearing aid fine-tuning is beneficial to the user. Conclusions: We conclude that prefitting counseling can be advantageous to hearing aid outcome and recommend the addition of prefitting counseling to address expectations associated with quality of life and self-image. The data emphasize the need to address unrealistic expectations prior to fitting hearing aids cautiously, so as not to decrease expectations to the extent of discouraging and demotivating the patient. Data also show that positive expectations regarding the impact hearing aids will have on psychosocial well-being are important for successful hearing aid outcome.

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