Implementation of strategy based on auditory model based wavelet transform speech processing on DSP dedicated to cochlear prosthesis

2009 ◽  
Author(s):  
Amira Derbel ◽  
Mohamed Ghorbel ◽  
Mounir Samet ◽  
Ahmed Ben Hamida
Keyword(s):  
Wavelet Transform ◽  
Speech Processing ◽  
Cochlear Prosthesis ◽  
Auditory Model ◽  
Model Based

Exploring Wavelet Transform Based Methodology for Cochlear Prosthesis Advanced Speech Processing Strategy

2014 ◽  
Vol 100 (2) ◽  
pp. 341-352
Author(s):  
Mohamed Ghorbel ◽  
Amira Derbel ◽  
Fathi Kallel ◽  
Mounir Samet ◽  
Ahmed Ben Hamida
Keyword(s):  
Wavelet Transform ◽  
Speech Processing ◽  
Processing Strategy ◽  
Cochlear Prosthesis

scholarly journals Open Quotient Measurements Based on Multiscale Product of Speech Signal Wavelet Transform

2007 ◽  
Vol 2007 ◽  
pp. 1-5 ◽  
Author(s):  
Aïcha Bouzid ◽  
Noureddine Ellouze
Keyword(s):  
Wavelet Transform ◽  
Relative Error ◽  
Speech Processing ◽  
Speech Signal ◽  
Accurate Estimation ◽  
Pitch Period ◽  
Open Time ◽  
Wide Range ◽  
Voiced Speech ◽  
Egg Signal

This paper describes a multiscale product method (MPM) for open quotient measure in voiced speech. The method is based on determining the glottal closing and opening instants. The proposed approach consists of making the products of wavelet transform of speech signal at different scales in order to enhance the edge detection and parameter estimation. We show that the proposed method is effective and robust for detecting speech singularity. Accurate estimation of glottal closing instants (GCIs) and opening instants (GOIs) is important in a wide range of speech processing tasks. In this paper, accurate estimation of GCIs and GOIs is used to measure the local open quotient (Oq) which is the ratio of the open time by the pitch period. Multiscale product operates automatically on speech signal; the reference electroglottogram (EGG) signal is used for performance evaluation. The ratio of good GCI detection is 95.5% and that of GOI is 76%. The pitch period relative error is 2.6% and the open phase relative error is 5.6%. The relative error measured on open quotient reaches 3% for the whole Keele database.

THE ADVANTAGE OFTHEWAVELET TRANSFORM IN PROCESSING OF SPEECH SIGNALS

2021 ◽  
Vol 4 (3) ◽  
pp. 37-41
Author(s):  
Sayora Ibragimova ◽  
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Speech Processing ◽  
High Performance ◽  
Speech Sound ◽  
Digital Signal ◽  
Speech Signals ◽  
Multi Scale ◽  
Processing Of Speech Signals

This work deals with basic theory of wavelet transform and multi-scale analysis of speech signals, briefly reviewed the main differences between wavelet transform and Fourier transform in the analysis of speech signals. The possibilities to use the method of wavelet analysis to speech recognition systems and its main advantages. In most existing systems of recognition and analysis of speech sound considered as a stream of vectors whose elements are some frequency response. Therefore, the speech processing in real time using sequential algorithms requires computing resources with high performance. Examples of how this method can be used when processing speech signals and build standards for systems of recognition.Key words: digital signal processing, Fourier transform, wavelet analysis, speech signal, wavelet transform

A transformation model based on dual-tree complex wavelet transform for non-rigid registration of 3D MRI images

2019 ◽  
Vol 17 (04) ◽  
pp. 1950025 ◽  
Author(s):  
Nima Torbati ◽  
Ahmad Ayatollahi
Keyword(s):  
Wavelet Transform ◽  
Magnetic Resonance Images ◽  
Transformation Model ◽  
Complex Wavelet Transform ◽  
Model Based ◽  
Current State ◽  
Gradient Descent Algorithm ◽  
Expansion Theory ◽  
Complex Wavelet ◽  
Spectral Transforms

Image registration is regarded as an important component of medical procedures. The present study aimed to introduce a new transformation model based on dual-tree complex wavelet transform (DT-CWT). To this aim, parametric registration methods was revised based on the function expansion theory and the gradient descent algorithm was used to introduce a general formulation for transformation models based on spatio-spectral transforms. Then, the performance of the proposed method was evaluated on a public dataset of 3D real magnetic resonance images (MRI) and compared with the transformation model based on wavelets. Finally, the performance of the proposed method was compared with the current state-of-the-art methods (IRTK, SyN and SPM-DARTEL). Based on the experimental results, the proposed method could deliver superior registration performance compared with the previous methods.

DSP-Based Implementation and Optimization of Auditory Filter-Bank

2013 ◽  
Vol 765-767 ◽  
pp. 2862-2865
Author(s):  
Jin Lun Chen
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Filter Bank ◽  
Audio Signal ◽  
Audio Signal Processing ◽  
Auditory Model ◽  
Auditory Filter ◽  
The Real ◽  
Model Based ◽  
Signal Processing Systems

The auditory filter-bank is the key component of auditory model, and its implementation involves a lot of computations. The time spent by an auditory filter-bank to finish its work has a significant effect on the real-time implementation of auditory model-based audio signal processing systems. In this paper, we give a brief introduction to the auditory filter-bank at the first, and then discuss its DSP-based implementation and optimization in details.

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