Borisagar K Speech Enhancement Techniques Digit Aids 2019 torrent

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​This book provides various speech enhancement algorithms for digital hearing aids. It covers information on noise signals extracted from silences of speech signal. The description of the algorithm used for this purpose is also provided. Different types of adaptive filters such as Least Mean Squares (LMS), Normalized LMS (NLMS) and Recursive Lease Squares (RLS) are described for noise reduction in the speech signals. Different types of noises are taken to generate noisy speech signals, and therefore information on various noises signals is provided. The comparative performance of various adaptive filters for noise reduction in speech signals is also described. In addition, the book provides a speech enhancement technique using adaptive filtering and necessary frequency strength enhancement using wavelet transform as per the requirement of audiogram for digital hearing aids.
Presents speech enhancement techniques for improving performance of digital hearing aids;
Covers various types of adaptive filters and their advantages and limitations;
Provides a hybrid speech enhancement technique using wavelet transform and adaptive filters.
The interference of background noise is the greatest problem reported by hearing aid wearers. Background noise is a combination of different frequencies; these unwanted frequencies reduce the precision of speech. A higher level of background noise degrades intelligibility. The speech signal is a quasi-periodic signal. If the speech signal is masked by noise, then the intelligence of that signal is reduced significantly and because of that, it is difficult to understand what is being said.
Moreover, the speech signal carries many redundant samples which masks a portion of the noise. Noisy signal can’t be easily detected by a person with a hearing disorder. It’s an irritating process between detecting intelligence from a noisy speech by those with hearing disorders whereas normal people can do this job easily.
A person with a hearing impairment, may find it cumbersome to identify specific frequencies in the presence of noise that contains basic frequencies. In that case, the speech signal is not audible; thus, it is not possible to interpret speech, and this may cause problems in everyday life. Any product associated with hearing aids needs more work on design in such a way that the effect of the noise would be reduced before any further modification. It is vital to observe the sound quality with the background noise.
Deafness is a conical disability due to either a sensory neural defect in which cells are dead because of age, or a major disease. Deafness can also be caused by problems with bone and air conduction. One of the methods to solving hearing disorders is by cochlear implants, but this requires surgery. As an alternative, most people wear hearing aids instead. Enhancement of noisy speech is possible in the case of hearing aids. Generally, different noises have affected various frequencies of the speech signal. Fixed filters can help a great deal when it comes to removing an unwanted noise frequency. However, there can be many variations of noise frequency and over time it may degrade the fixed filter. It can be seen that with an unwanted signal, the speech component is also affected. With that constraint, the use of filtering techniques that are only applicable to the incoming noise signal is required. In addition to this, as per the noise characteristics, the filtering process should be adaptive.
Sound
Ear Structure and Its Workings
Hearing Impaired
Audiogram
Digital Hearing Aids
Issues in Digital Hearing Aids
Generation of Speech Signal and Its Characteristics
Speech Signal
Major Features of Speech Articulation .
Properties and Characteristics of Speech Signal
Introduction of Adaptive Filters and Noises for Speech
Adaptive Filter
LMS Adaptive Filter
Descent Algorithm
Normalized Least Mean Square (NLMS) Adaptive Filter
Mean Value
Mean Square Deviation of the RLS Algorithm
Ensemble Average Learning Curve of the
RLS Algorithm
Noise
Fourier Transform, Short-Time Fourier Transform,
and Wavelet Transform
Fourier Transform (FT)
Short-Time FT
Wavelet Transform (WT)
Comparison of the Wavelet Transform (WT)
with FT and STFT .
Speech Signal Enhancement Using Adaptive Filters
Introduction
Steps for Speech Enhancement Process
Implementation Flow of VAD Algorithm
Speech Enhancement Process based on LMS Algorithm
Comparative Analysis of Simulation Results
References
Speech Signal Enhancement Based on Wavelet Transform
Procedure for Speech Signal Enhancement Using
Wavelet Transform
Implementation and Results of Speech Signal
Enhancement Using Wavelet Transform
Summary of This Book and Future Research Directions
Important Points Covered in the Book
Future Research Direction