Voice signal processing pdf

Applied Acoustics. View 1 excerpt, cites methods. ACM Trans. Internet Techn. A study of using cough sounds and deep neural networks for the early detection of Covid Biomedical Engineering Advances. The current clinical diagnosis of COVID requires person-to-person contact, needs variable time to produce results, and is expensive. It is even inaccessible to the general population in some … Expand.

Intelligent Pathological voice detection. View 1 excerpt, references background. Reliable, automatic and objective detector of pathological voice disorders from speech signals is a long sought-for tool, by voice clinicians as well as by general practitioners. Such a detector can … Expand. Computer aided recognition of pathological voice. Laryngeal diseases and vocal fold pathologies have strong impacts in the resulting quality of the voice production.

Many approaches have been developed to analyze the acoustic parameters for the … Expand. Parametric cepstral analysis for pathological voice assessment. SAC ' View 1 excerpt, references methods. Voice diseases are increasing dramatically, due mainly to unhealthy social habits and voice abuse. In this paper, we investigate the methods of acoustic voice analysis AVA with adaptive features to … Expand.

Highly Influential. View 30 excerpts, references background and methods. Medicine, Computer Science. Journal of voice : official journal of the Voice Foundation.

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Corresponding commands are : facilities, analyse and processing facilities. User Wave structure parameters have following meaning: can display current frequency and spectrum value interractive wFormatTag is type of Waveform-audio format, way on mouse moving in spectral displaying area ; nChannels specifies number of channels, - changing wave displaying resolution : ZOOM IN — nSamplesPerSec represents sampling rate, increases displaying resolution of current window applies for nAvgBytesPerSec is data rate, wave, amplitude and phase windows.

Command reduces nBlockAlign is data block alignment, window dimension in the benefit of analyse precision ; wBitsPerSample gives sampling bit resolution, ZOOM OUT is the complementary command, decreasing displaying resolution of current window ; zoom out increases amount of information displaying in the window, but reduces analyse precision.

It is used for progressive increasing of analyse dimension by adding samples one by one in analyse window. This command provides interactive filtering of frequencies and graphical editing of speech signal formants and harmonics. Figure 1. This rule applies only for voiced segments of First of all user will open a speech signal recording from a speech, because consonants or vocal noises have no WAVE file.

Speech wave will be displayed in the upper part fundamental frequency. Calculus of spectra is limited to 16k figure 2. In Hz, Hz.

Fundamental frequency is given in this case by the most cases this value is quite enough for spectral analysis the frequence of the first formant: Hz. Magnitude of current window will be displayed in the status bar. Tw parameter indicates dimension in time units seconds, milliseconds and microseconds , and Nw parameter shows sampling dimension. Sampling frequency will be also shown in FFT displaying zone, by Fs parameter. Sampling frequency doubles spectral window magnitude because of FFT mirroring effect: spectrum values are symmetrical from a value that equals middle of sampling frequency.

So spectral window is calculated to display only first half of spectrum values. FFT displaying zone will show also spectral resolution, that is frequency distance between two consecutive values of spectrum. For analysing specific segments of speech signal, SPE application allows windowed analysis. User can select interactive way an analyse window and automatically adjust window borders to zero crossing values.

This fact gives a maximum precision in computing the FFT spectrum, and so Figure 2. Formants and fundamental frequency of a voiced segment of Gaussian windowing method is not necessary.

Rules for speech computing FFT spectra are the following: 1 if no selection exists, then spectra are calculated on As previously said, SPE application allows selective current displayed window; frequence filtering and spectrum editing, very important for 2 if user has selected a distinct analyse zone, spectra are speech analysis and signal enhancement.

Application will display as default all the three remove bands of frequencies for noise suppression or analyse windows. By moving mouse pointer on the amplitude or User can also modify spectrum formants or harmonics in phase spectrum, user gets the precise values of frequencies order to modify sound timbre and will be able for immediate and magnitude of spectrum, amplitude or phase.

The experiments Once a WAVE file has been loaded and speech signal was that have been done show that a good quality voice own a displayed, application will display both amplitude and phase rich set of harmonics. Especially high order harmonics are signal spectra.

Into speech analysing, more important is determinative for quality of speech. This is useful inside the amplitude spectrum, that gives information about the quality process of creating a vocal database used in speech synthesis, of speech. By analysing this amplitude spectrum, one can get where some vocal segments could be enriched by adding important parameters of speech: fundamental frequency higher harmonics.

Application automatically detects formants or local In the second case, the perception of sound is better. Magnitude, central frequence formant frequence. The goal of these experiments was We have described in this paper an original application to determine specific characteristics of speech signal named Signal Processing and Enhancement Application - corresponding with pronunciation of various phonemes in SPE, designed for analysing and processing of speech signal.

Romanian by distinct speakers. We have presented main facilities of the application and also Vocal signal was recorded by the mean of an unidirectional how to work with application. In future articles we will present the whole set of Soundblaster. There have been also analysed audio signal experiments used for speech synthesys. Thus, we have accomplished following analyses: Teora, [2] E. Lupu, P. We have also done vowel sound analyses specific for Romanian speech synthesis.

In this way we have studied the characteristics of Romanian vowel sounds in different phonetic and prosodic contexts.