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International Journal of Engineering Inventions
e-ISSN: 2278-7461, p-ISSN: 2319-6491
Volume 3, Issue 6 (January 2014) PP: 36-40

Telemonitoring of Four Characteristic Parameters of Acoustic
Vocal Signal in Patients with Tumor or Inflammatory Chronic
Dysphonia
S. Abdelouahed1, Pr. M. Benabdallah2, S. Aounallah3, Pr. F. Hadj Allal4
1,2

Faculty of Technology, Laboratory of Biomedical Engineering, University of Tlemcen, Algeria
3,4
Faculty of Medicine, University Hospital of Tlemcen, University of Tlemcen, Algeria

Abstract: In this paper we develop a system dedicated to the objective characterization of dysphonia chronic
laryngeal origin. The purpose of this system is threefold: diagnosis, treatment and monitoring of patient. For
that we design an experimental protocol which consists of the recording and the archiving of the acoustic voice
signal by means of the software environment Audacity which makes it possible to deliver a temporal signal
under format WAVE. Our contribution consisted of the implementation, under the Visual Basic environment, of
an algorithm that allows performing the analysis of a spectro-temporal acoustic voiced speech signal in this
case the vowel "a" sustained for three seconds.
We applied this algorithm on 10 healthy subjects and 10 pathological subjects of whose 7 with cancer
of the larynx, one with chronic laryngitis and one presenting an inflammatory polyp of the vocal cords. The
results obtained show a variability of spectro-temporal characteristics between healthy and pathological
subjects and prone pathological between them according to the nature of the lesion in particular with regard to
spectral content evaluated by Short-Time discrete Fourier Transform STD.FT, Disturbances in the medium term
STD, Disturbance of short-term speech signal (jitter) and the fundamental frequency Fs averaged over several
frames of the voiced signal.
Keywords: STD, STD- FT, dysphonia laryngeal, voiced sound; jitter, fundamental frequency.

I.

Introduction

Assessing the quality of voice and perception of the causes of its degradation through various indices
voice has always been the main concern clinical speech pathologists. However, the voice and speech is in
essence made to be heard, the subjective evaluation "listening" to "clinical ear" of the expert remains the
reference face of objective assessment methods. Today, the voice treatment is a fundamental component of the
engineers sciences .it takes place between digital and language treatment i.e. (symbolical data treatment), since
the 60‟s, this scientific field has known a dazzling expansion linked to the development of the information and
communication technical tools [1][4]. Among the voice treatment applications we distinguish [5] [6]:
1) Temporal spatio-spectro analysis of the vocal signal observing the objective characterization of dysphonia of
laryngeal origins [9] [10].
2) Quantitative estimation of characteristics parameters of the vocal signal during its acoustical representation
especially the fundamental frequency of voiced sounds and its dispersion expressed by the factor STD, tones,
formant, jitter and shimmer [7][11][12].

II.

Materiel And Methodes

A telemedical plat-form was realized to the acquisition ,archiving and speech signals transfer also to
construct an interactive data base in order to explore , observe the dysphonia of laryngeal origin and supervise
the treatment especially tumors cases. According to this we‟ve developed an algorithm that takes care of:
1. The transformation of the format WAVES to the
HEXADECIMAL one coded upon the 16 bits with a sample frequency of 8KHZ.
2. The calculation of the discrete Fourier transform in reduced delay STD.FT according to the order 12 [13]
[8].
3. The calculation of the averaged fundamental frequency on 6 selections (moving average), jitter and STD.
4. The adjustment of interactive data base of acoustical vocals signals physiological and pathological
according to a clinical, epidemiological study for a best therapeutically taking charge.

www.ijeijournal.com

Page | 36
Telemonitoring of Four Characteristic Parameters of Acoustics Vocal Signal in Patients…
2.1. Algorithm of the STD.FT[2][3]
Input speech signal f (t)

Input F (f)

Sampling
𝑓 𝑡 = 𝑓 𝑡 . 𝜔 𝑡,𝑇 𝑠

Sampling
𝐹 𝑓 = 𝐹 𝑓 ∗ 𝛺 𝑓,𝐹 𝑠

Limitation of the duration
𝑓 𝑇0 (𝑡) = 𝑓 𝑡 . 𝜋 𝑇0 (𝑡)

Spectral repetition
𝐹𝑎 𝑓 = 𝐹𝑒

𝐹𝑎 (𝑓 − 𝑛. 𝐹𝑠 )
𝑛 ⋴𝕫

Periodization
𝑓 𝑇0𝑝 𝑡 = 𝑓 𝑡 . 𝜋 𝑇0 𝑡 ∗ 𝜔 𝑡,𝑇 𝑠

Sampling frequency
𝐹𝑎𝑝 𝑓 = 𝑓 𝑓 ∗ 𝐹𝑠

𝐹𝑎 𝑓 − 𝑛. 𝐹𝑠 . 𝛺 𝑓,𝐹 𝑠
𝑛⋴𝑧

STD.FT
𝑁−1

𝑓(𝑘) . 𝑒 −𝑗 2𝜋

𝐹 𝑛 =
𝑘=0

n=0, 1, 2….. (N-1)

𝑁=

𝑛
𝑘
𝑁
𝑇0
𝑇𝑠

= 𝑇0

2.2. Global algorithm of the application:
Recording the vocal signal via Audacity software
Data conversions from the format WAVE to hexadecimal one
The signal windowing

The signal layout

The Calculation and the layout of the STD.FT

Calculation of jitter

Calculation of STD

Calculates the average
fundamental frequency

2.3. Sample presentation
The incoming corpus in the experimental protocol constitute of:
The tenth subjects don‟t represent a particular laryngeal pathology (six subjects of masculine sex and
tow one feminine sex aged from 40 to 60 years old)
Tenth subjects of masculine sex patients aged from 40 to 80 years old (six subjects represent larynx
cancer in the third and fourth stage, a three case of chronicle laryngitis and a case of inflamed polyps of vocal
cords).

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Telemonitoring of Four Characteristic Parameters of Acoustics Vocal Signal in Patients…
III.

Results And Clinical Evaluation

Fig.1: Temporal layout of vocal signal of a
healthy subject

Fig. 2: Frequency layout of vocal signal of a
healthy subject

The average fundamental frequency is: 200.60 HZ jitter: 069sec and STD: 13.94Hz

Fig.3: Temporal layout of vocal signal of a subject
whose attains a larynx cancer

Fig.4: Frequency layout of vocal signal of a subject
whose attains a larynx cancer

The average fundamental frequency is: 62.48 Hz, jitter is: 2.62sec and STD is: 4.5Hz

Fig.5: Temporal layout of vocal signal of a subject
whose attains an inflamed polyps

Fig. 6: frequency layout of vocal signal of a subject
whose attains an inflamed polyps

The average fundamental frequency is: 118.80 HZ. Jitter is: 1.59sec and STD is: 9.97Hz
3.1. Distant sustained of the patient
The patient treated by the radiotherapy (persons suffering from cancer) or by medical treatment (a
patient presents a clinical inflamed syndrome) and whose living in isolated area especially the north polar could
be distant sustained thank to platform implantation at near the health centers .And thank to the periodical
recording of the acoustical signal vocal according to the precedent described protocol and its O.R.L
department of University Hospital accordance with the architecture client-server hold up by the component
Winsock compatible with the protocol TCP/IP which permitted the transmission of the data toward intranet
or internet thus the patient avoiding the inutile movement a condition that he responds favorably to the
instituted treatment.

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Telemonitoring of Four Characteristic Parameters of Acoustics Vocal Signal in Patients…
IV.

Summary Of Results

Table 1 : The jitter, STD and the average fundamental frequency of healthy subjects

Healthy subjects
Fundamental
frequencies Fs(HZ)

1st
subject

2nd
subject

3rd
subject

4th
subject

5th
subject

6th
subject

7th
subject

8th
subject

9th
subject

Male sexe

10th
subject

Female sexe

1stselection
2nd selection
3rd selection
4th selection
5th selection
6th selection
The average fundamental
frequencies (HZ)

227.05
184.81
184.81
227.05
195.12
184.8
200.6

200.65
211.2
184.8
184.8
211 .4
195.37
198.03

190.09
184.8
184.8
216.49
184.81
211.21
196.68

184.81
211.21
179.53
184.81
211.21
184.8
192.72

216.49
184.81
200.65
221.77
200.65
184.81
201.53

205.93
179.53
221.77
205.93
184.81
205.93
200.65

184.81
205.93
227.05
211.21
195.37
195.37
203.29

211.21
190.09
195.37
216.49
179.53
195.37
198.01

200.65
211.2
184.8
184.8
184.81
195.37
193.59

190.09
184.8
184.8
216.49
184.81
211.21
195.36

Jitter (sec)

0.69

0.67

0.68

0.67

0.77

0.68

0.61

0.79

0.7

0.68

STD (sec)

13.94

13.58

13.29

13.2

12.93

13.49

13.17

13.17

12.44

13.28

Table 2 : The jitter, STD and the average fundamental frequency of sick subjects

sick subjects
Fundamental
frequencies Fs (HZ)
1stselection
2nd selection
3rd selection
4th selection
5th selection
6th selection
The average fundamental
frequencies (HZ)
Jitter (sec)
STD (sec)

1st
subject

2nd
subject

3rd
subject

4th
subject

5th
subject

6th
subject

7th
subject

Larynx cancer

8th
subject

9th
subject

10th
subject

Inflammatory pathology

73.92
73.92

58.08
47.52

68.64
47.52

47.52
52.8

47.52
63.36

50.52
67.36

105.6
147.85

121.44
105.6

105.6
137.29

174.25
163.69

52.8
73.92
63.36
73.92
68.64

47.5
.24
42.24
47.52
47.51

47.52
68.64
68.64
73.92
62.48

52.8
47.58
58.08
58.08
52.81

47.52
58.08
63.36
68.64
58.08

50.52
58.08
68.64
47.52
57.10

126.73
142.57
105.6
110.88
123.20

110.88
100.32
137.29
137.29
118.8

126.73
110.88
121.44
105.6
117.92

142.57
174.81
163.69
142.57
160.17

2.64

2.22

2.62

2.4

2.69

2.65

1.5

1.59

1.03

2.69

4.97

5.28

4.5

4.29

4.31

4.78

8.97

9.97

8.13

10.31

4.1. Results discussions:
This work was done in collaboration with doctors in ORL, ORL department of the University Hospital Tlemcen.
 In healthy subjects, the fundamental frequency was situated around 200 Hz, STD about 13Hz and Jitter
extend to 0.7 sec Corresponding to the physiological frequency of vowel „a‟.
 In patients with the cancer of vocal cords, the fundamental frequency was significantly reduced to 60 Hz,
while the STD was greatly decreased to 4Hz, and the jitter was increased to 2.5 sec.
 In the inflammatory polyp of vocal cords, fundamental frequency slightly decreased to 160 Hz, while STD
was slightly decreased to 10 Hz. and jitter was slightly increased to 1.03sec.
 In patients with inflammatory disease (chronic laryngitis), the fundamental frequency was reduced to
120Hz, and STD decrease around 8 Hz and jitter was increased slightly to 1.5 Sec
 The spectral range was significantly diminished in cancer patients due to the total absence of vibration of
vocal cords. This limitation of frequency range was also present but truncated in the case of chronic
inflammatory disease of the larynx.

V.

Conclusion

The analysis of the signal vocal treatment in accordance with screening and sustain of the vocals
dysphonia stay a vast domain of research.
The aim of this work was to design and implement a human-machine interface dedicated to the
objective evaluation of laryngeal dysphonia through the spectro-temporal characterization of the acoustic vocal
signal.
For this we have developed:
 An acquisition system using the sound card-driven by environment software Audacity permitted in
particular a passer-by sonorous bandaged extending from 0 to 4 kHz with a sampling frequency of 8 kHz
and a voice signal recording format WAVE.
 A WAVE format converted to HEX format16-bit
www.ijeijournal.com

Page | 39
Telemonitoring of Four Characteristic Parameters of Acoustics Vocal Signal in Patients…







An experimental protocol based on the emission of a sustained voiced sound for 3 seconds in the
occurrence the vowel 'a' the most commonly used in this kind of exploration of the voice. An application of
digital treatment of the vocal signal by implementing an algorithm for calculating the Short-Time discrete
Fourier Transform (STD.FT) and the detection of the jitter, STD and the fundamental frequency (Fs)
averaged over 6 frames. This represents the frequency factor of the sound at around 200 Hz, the STD 13 Hz
and the jitter at around 0.7 Sec in adult healthy subject.
Results in concordance with those are found in the bibliography
The jitter, STD and the fundamental frequency present a large variability in subjects with vocal cord
pathology.
This variability of parameters (Fs, jitter, STD) seems largely different depending on the type of disease that
is inflammatory or tumor.
These recordings performed in vivo and in situ at the ORL department of the University Hospital Tlemcen
allowed us to start developing a database on classification of laryngeal pathologies as inflammatory or
tumor type for an early detection of laryngeal cancer and its prevention by the epidemiological study of
predisposing factors.

REFERENCES
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]

[9]

[10]
[11]
[12]
[13]

A.Drygajlo, « Traitement de la parole »-Partie 1-, école Polytechniques Fédérale de Lausane EPFL, 1998.Albert, R.; Jeong, H.;
Barab´asi, A.-L. Diameter of the world-wide Web. Nature,1999, 401, pp. 130–131.
L.Benlaldj, « Etude de la méthode PLP (Perceptual linear prediction) en reconnaissance automatique de la parole », Thèse de
magister en électronique, spécialité : Signaux et Systèmes, promotion 1999/2000.
LAKHDAR Mohammed Hicham, HASSAM Ahmed, « classification des sons de la parole par la technique PLP », Mémoire de fin
d‟étude pour l‟obtention du diplôme d‟ingénieur d‟état en contrôle, Université ABOU BEKER BELKIAD TELEMCEN ,2001.
Calliope, la parole et son traitement automatique, Ed. Masson, 1989.
T. Dutoit, « Introduction au Traitement Automatique de la Parole », Notes de cours, Faculté Polytechnique de Mons, 2000.
Dr. ANDRZEJ DRYGAJLO, « TRAITEMENT DE LA PAROLE », “Interactive Multimodal Information Management (IM)2” ,
Laboratory of IDIAP (LIDIAP) Institute of Electrical Engineering (IEL) ,Swiss Federal Institute of Technology .
Dr Camille Finck, chapitre sur « L‟évaluation fonctionnelle des dysphonie d‟origine laryngé », Service d'Oto-rhino-laryngologie,
CHU sart Tilman, Université de Liège, Liège, Belgium.
GHIO, A.; GIOVANNI, A.; TESTON, B.; RÉVIS, J.; YU, P.; OUAKNINE, M.; ROBERT, D.; LEGOU, T. Bilan et perspectives de
quinze ans d‟évaluation vocale par méthodes instrumentales et perceptives. Actes, Journées d'Etude sur la Parole (JEP) (27 : 2008
juin 9-13 : Avignon, FRANCE). . Avignon: LIA. 2008
GHIO, A.; POUCHOULIN, G.; GIOVANNI, A.; FREDOUILLE, C.; TESTON, B.; RÉVIS, J.; BONASTRE, J.-F.; ROBERT, D.;
YU, P.; OUAKNINE, M.; GUARELLA, M.-D.; SPEZZA, C.; LEGOU, T.; MARCHAL, A. Approches complémentaires pour
l'évaluation des dysphonies : bilan méthodologique et perspectives. Travaux Interdisciplinaires du Laboratoire Parole et Langage
d'Aix-en-Provence (TIPA), vol. 26. 2008, p. 33-74.
YU P., GARREL R., NICOLLAS R., OUAKNINE M., GIOVANNI A., (2007), "Objective voice analysis in dysphonic patients.
New data including non linear measurements", Folia Phoniatrica et Logopaedica, 59:20-30. Lausanne (EPFL).
Giovanni A., Yu P., Révis J., Guarella MD., Teston B., Ouaknine M. (2006). "Analyse objective des dysphonies avec l'appareillage
EVA. Etat des lieux.", Revue Oto-Rhino-Laryngologie Française, 90, p3 183-192.
TESTON, B. L'évaluation instrumentale des dysphonies. Etat actuel et perspectives. In Giovanni A. (ed.) Le bilan d'une dysphonie.
ISBN 2-914513-62-3. Marseille: Solal. 2004, p. 105-169.
VIALLET, F.; TESTON, B. Objective evaluation of dysphonia: acoustic and aerodynamic methods. Proceedings of European
Laryngological Society: Around dysphasia, dysarthria, dysphonia (2003: Toulouse, FRANCE). 2003, p. 53-55.

.

www.ijeijournal.com

Page | 40

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Telemonitoring of Four Characteristic Parameters of Acoustic Vocal Signal in Patients with Tumor or Inflammatory Chronic Dysphonia

  • 1. International Journal of Engineering Inventions e-ISSN: 2278-7461, p-ISSN: 2319-6491 Volume 3, Issue 6 (January 2014) PP: 36-40 Telemonitoring of Four Characteristic Parameters of Acoustic Vocal Signal in Patients with Tumor or Inflammatory Chronic Dysphonia S. Abdelouahed1, Pr. M. Benabdallah2, S. Aounallah3, Pr. F. Hadj Allal4 1,2 Faculty of Technology, Laboratory of Biomedical Engineering, University of Tlemcen, Algeria 3,4 Faculty of Medicine, University Hospital of Tlemcen, University of Tlemcen, Algeria Abstract: In this paper we develop a system dedicated to the objective characterization of dysphonia chronic laryngeal origin. The purpose of this system is threefold: diagnosis, treatment and monitoring of patient. For that we design an experimental protocol which consists of the recording and the archiving of the acoustic voice signal by means of the software environment Audacity which makes it possible to deliver a temporal signal under format WAVE. Our contribution consisted of the implementation, under the Visual Basic environment, of an algorithm that allows performing the analysis of a spectro-temporal acoustic voiced speech signal in this case the vowel "a" sustained for three seconds. We applied this algorithm on 10 healthy subjects and 10 pathological subjects of whose 7 with cancer of the larynx, one with chronic laryngitis and one presenting an inflammatory polyp of the vocal cords. The results obtained show a variability of spectro-temporal characteristics between healthy and pathological subjects and prone pathological between them according to the nature of the lesion in particular with regard to spectral content evaluated by Short-Time discrete Fourier Transform STD.FT, Disturbances in the medium term STD, Disturbance of short-term speech signal (jitter) and the fundamental frequency Fs averaged over several frames of the voiced signal. Keywords: STD, STD- FT, dysphonia laryngeal, voiced sound; jitter, fundamental frequency. I. Introduction Assessing the quality of voice and perception of the causes of its degradation through various indices voice has always been the main concern clinical speech pathologists. However, the voice and speech is in essence made to be heard, the subjective evaluation "listening" to "clinical ear" of the expert remains the reference face of objective assessment methods. Today, the voice treatment is a fundamental component of the engineers sciences .it takes place between digital and language treatment i.e. (symbolical data treatment), since the 60‟s, this scientific field has known a dazzling expansion linked to the development of the information and communication technical tools [1][4]. Among the voice treatment applications we distinguish [5] [6]: 1) Temporal spatio-spectro analysis of the vocal signal observing the objective characterization of dysphonia of laryngeal origins [9] [10]. 2) Quantitative estimation of characteristics parameters of the vocal signal during its acoustical representation especially the fundamental frequency of voiced sounds and its dispersion expressed by the factor STD, tones, formant, jitter and shimmer [7][11][12]. II. Materiel And Methodes A telemedical plat-form was realized to the acquisition ,archiving and speech signals transfer also to construct an interactive data base in order to explore , observe the dysphonia of laryngeal origin and supervise the treatment especially tumors cases. According to this we‟ve developed an algorithm that takes care of: 1. The transformation of the format WAVES to the HEXADECIMAL one coded upon the 16 bits with a sample frequency of 8KHZ. 2. The calculation of the discrete Fourier transform in reduced delay STD.FT according to the order 12 [13] [8]. 3. The calculation of the averaged fundamental frequency on 6 selections (moving average), jitter and STD. 4. The adjustment of interactive data base of acoustical vocals signals physiological and pathological according to a clinical, epidemiological study for a best therapeutically taking charge. www.ijeijournal.com Page | 36
  • 2. Telemonitoring of Four Characteristic Parameters of Acoustics Vocal Signal in Patients… 2.1. Algorithm of the STD.FT[2][3] Input speech signal f (t) Input F (f) Sampling 𝑓 𝑡 = 𝑓 𝑡 . 𝜔 𝑡,𝑇 𝑠 Sampling 𝐹 𝑓 = 𝐹 𝑓 ∗ 𝛺 𝑓,𝐹 𝑠 Limitation of the duration 𝑓 𝑇0 (𝑡) = 𝑓 𝑡 . 𝜋 𝑇0 (𝑡) Spectral repetition 𝐹𝑎 𝑓 = 𝐹𝑒 𝐹𝑎 (𝑓 − 𝑛. 𝐹𝑠 ) 𝑛 ⋴𝕫 Periodization 𝑓 𝑇0𝑝 𝑡 = 𝑓 𝑡 . 𝜋 𝑇0 𝑡 ∗ 𝜔 𝑡,𝑇 𝑠 Sampling frequency 𝐹𝑎𝑝 𝑓 = 𝑓 𝑓 ∗ 𝐹𝑠 𝐹𝑎 𝑓 − 𝑛. 𝐹𝑠 . 𝛺 𝑓,𝐹 𝑠 𝑛⋴𝑧 STD.FT 𝑁−1 𝑓(𝑘) . 𝑒 −𝑗 2𝜋 𝐹 𝑛 = 𝑘=0 n=0, 1, 2….. (N-1) 𝑁= 𝑛 𝑘 𝑁 𝑇0 𝑇𝑠 = 𝑇0 2.2. Global algorithm of the application: Recording the vocal signal via Audacity software Data conversions from the format WAVE to hexadecimal one The signal windowing The signal layout The Calculation and the layout of the STD.FT Calculation of jitter Calculation of STD Calculates the average fundamental frequency 2.3. Sample presentation The incoming corpus in the experimental protocol constitute of: The tenth subjects don‟t represent a particular laryngeal pathology (six subjects of masculine sex and tow one feminine sex aged from 40 to 60 years old) Tenth subjects of masculine sex patients aged from 40 to 80 years old (six subjects represent larynx cancer in the third and fourth stage, a three case of chronicle laryngitis and a case of inflamed polyps of vocal cords). www.ijeijournal.com Page | 37
  • 3. Telemonitoring of Four Characteristic Parameters of Acoustics Vocal Signal in Patients… III. Results And Clinical Evaluation Fig.1: Temporal layout of vocal signal of a healthy subject Fig. 2: Frequency layout of vocal signal of a healthy subject The average fundamental frequency is: 200.60 HZ jitter: 069sec and STD: 13.94Hz Fig.3: Temporal layout of vocal signal of a subject whose attains a larynx cancer Fig.4: Frequency layout of vocal signal of a subject whose attains a larynx cancer The average fundamental frequency is: 62.48 Hz, jitter is: 2.62sec and STD is: 4.5Hz Fig.5: Temporal layout of vocal signal of a subject whose attains an inflamed polyps Fig. 6: frequency layout of vocal signal of a subject whose attains an inflamed polyps The average fundamental frequency is: 118.80 HZ. Jitter is: 1.59sec and STD is: 9.97Hz 3.1. Distant sustained of the patient The patient treated by the radiotherapy (persons suffering from cancer) or by medical treatment (a patient presents a clinical inflamed syndrome) and whose living in isolated area especially the north polar could be distant sustained thank to platform implantation at near the health centers .And thank to the periodical recording of the acoustical signal vocal according to the precedent described protocol and its O.R.L department of University Hospital accordance with the architecture client-server hold up by the component Winsock compatible with the protocol TCP/IP which permitted the transmission of the data toward intranet or internet thus the patient avoiding the inutile movement a condition that he responds favorably to the instituted treatment. www.ijeijournal.com Page | 38
  • 4. Telemonitoring of Four Characteristic Parameters of Acoustics Vocal Signal in Patients… IV. Summary Of Results Table 1 : The jitter, STD and the average fundamental frequency of healthy subjects Healthy subjects Fundamental frequencies Fs(HZ) 1st subject 2nd subject 3rd subject 4th subject 5th subject 6th subject 7th subject 8th subject 9th subject Male sexe 10th subject Female sexe 1stselection 2nd selection 3rd selection 4th selection 5th selection 6th selection The average fundamental frequencies (HZ) 227.05 184.81 184.81 227.05 195.12 184.8 200.6 200.65 211.2 184.8 184.8 211 .4 195.37 198.03 190.09 184.8 184.8 216.49 184.81 211.21 196.68 184.81 211.21 179.53 184.81 211.21 184.8 192.72 216.49 184.81 200.65 221.77 200.65 184.81 201.53 205.93 179.53 221.77 205.93 184.81 205.93 200.65 184.81 205.93 227.05 211.21 195.37 195.37 203.29 211.21 190.09 195.37 216.49 179.53 195.37 198.01 200.65 211.2 184.8 184.8 184.81 195.37 193.59 190.09 184.8 184.8 216.49 184.81 211.21 195.36 Jitter (sec) 0.69 0.67 0.68 0.67 0.77 0.68 0.61 0.79 0.7 0.68 STD (sec) 13.94 13.58 13.29 13.2 12.93 13.49 13.17 13.17 12.44 13.28 Table 2 : The jitter, STD and the average fundamental frequency of sick subjects sick subjects Fundamental frequencies Fs (HZ) 1stselection 2nd selection 3rd selection 4th selection 5th selection 6th selection The average fundamental frequencies (HZ) Jitter (sec) STD (sec) 1st subject 2nd subject 3rd subject 4th subject 5th subject 6th subject 7th subject Larynx cancer 8th subject 9th subject 10th subject Inflammatory pathology 73.92 73.92 58.08 47.52 68.64 47.52 47.52 52.8 47.52 63.36 50.52 67.36 105.6 147.85 121.44 105.6 105.6 137.29 174.25 163.69 52.8 73.92 63.36 73.92 68.64 47.5 .24 42.24 47.52 47.51 47.52 68.64 68.64 73.92 62.48 52.8 47.58 58.08 58.08 52.81 47.52 58.08 63.36 68.64 58.08 50.52 58.08 68.64 47.52 57.10 126.73 142.57 105.6 110.88 123.20 110.88 100.32 137.29 137.29 118.8 126.73 110.88 121.44 105.6 117.92 142.57 174.81 163.69 142.57 160.17 2.64 2.22 2.62 2.4 2.69 2.65 1.5 1.59 1.03 2.69 4.97 5.28 4.5 4.29 4.31 4.78 8.97 9.97 8.13 10.31 4.1. Results discussions: This work was done in collaboration with doctors in ORL, ORL department of the University Hospital Tlemcen.  In healthy subjects, the fundamental frequency was situated around 200 Hz, STD about 13Hz and Jitter extend to 0.7 sec Corresponding to the physiological frequency of vowel „a‟.  In patients with the cancer of vocal cords, the fundamental frequency was significantly reduced to 60 Hz, while the STD was greatly decreased to 4Hz, and the jitter was increased to 2.5 sec.  In the inflammatory polyp of vocal cords, fundamental frequency slightly decreased to 160 Hz, while STD was slightly decreased to 10 Hz. and jitter was slightly increased to 1.03sec.  In patients with inflammatory disease (chronic laryngitis), the fundamental frequency was reduced to 120Hz, and STD decrease around 8 Hz and jitter was increased slightly to 1.5 Sec  The spectral range was significantly diminished in cancer patients due to the total absence of vibration of vocal cords. This limitation of frequency range was also present but truncated in the case of chronic inflammatory disease of the larynx. V. Conclusion The analysis of the signal vocal treatment in accordance with screening and sustain of the vocals dysphonia stay a vast domain of research. The aim of this work was to design and implement a human-machine interface dedicated to the objective evaluation of laryngeal dysphonia through the spectro-temporal characterization of the acoustic vocal signal. For this we have developed:  An acquisition system using the sound card-driven by environment software Audacity permitted in particular a passer-by sonorous bandaged extending from 0 to 4 kHz with a sampling frequency of 8 kHz and a voice signal recording format WAVE.  A WAVE format converted to HEX format16-bit www.ijeijournal.com Page | 39
  • 5. Telemonitoring of Four Characteristic Parameters of Acoustics Vocal Signal in Patients…      An experimental protocol based on the emission of a sustained voiced sound for 3 seconds in the occurrence the vowel 'a' the most commonly used in this kind of exploration of the voice. An application of digital treatment of the vocal signal by implementing an algorithm for calculating the Short-Time discrete Fourier Transform (STD.FT) and the detection of the jitter, STD and the fundamental frequency (Fs) averaged over 6 frames. This represents the frequency factor of the sound at around 200 Hz, the STD 13 Hz and the jitter at around 0.7 Sec in adult healthy subject. Results in concordance with those are found in the bibliography The jitter, STD and the fundamental frequency present a large variability in subjects with vocal cord pathology. This variability of parameters (Fs, jitter, STD) seems largely different depending on the type of disease that is inflammatory or tumor. These recordings performed in vivo and in situ at the ORL department of the University Hospital Tlemcen allowed us to start developing a database on classification of laryngeal pathologies as inflammatory or tumor type for an early detection of laryngeal cancer and its prevention by the epidemiological study of predisposing factors. REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] A.Drygajlo, « Traitement de la parole »-Partie 1-, école Polytechniques Fédérale de Lausane EPFL, 1998.Albert, R.; Jeong, H.; Barab´asi, A.-L. Diameter of the world-wide Web. Nature,1999, 401, pp. 130–131. L.Benlaldj, « Etude de la méthode PLP (Perceptual linear prediction) en reconnaissance automatique de la parole », Thèse de magister en électronique, spécialité : Signaux et Systèmes, promotion 1999/2000. LAKHDAR Mohammed Hicham, HASSAM Ahmed, « classification des sons de la parole par la technique PLP », Mémoire de fin d‟étude pour l‟obtention du diplôme d‟ingénieur d‟état en contrôle, Université ABOU BEKER BELKIAD TELEMCEN ,2001. Calliope, la parole et son traitement automatique, Ed. Masson, 1989. T. Dutoit, « Introduction au Traitement Automatique de la Parole », Notes de cours, Faculté Polytechnique de Mons, 2000. Dr. ANDRZEJ DRYGAJLO, « TRAITEMENT DE LA PAROLE », “Interactive Multimodal Information Management (IM)2” , Laboratory of IDIAP (LIDIAP) Institute of Electrical Engineering (IEL) ,Swiss Federal Institute of Technology . Dr Camille Finck, chapitre sur « L‟évaluation fonctionnelle des dysphonie d‟origine laryngé », Service d'Oto-rhino-laryngologie, CHU sart Tilman, Université de Liège, Liège, Belgium. GHIO, A.; GIOVANNI, A.; TESTON, B.; RÉVIS, J.; YU, P.; OUAKNINE, M.; ROBERT, D.; LEGOU, T. Bilan et perspectives de quinze ans d‟évaluation vocale par méthodes instrumentales et perceptives. Actes, Journées d'Etude sur la Parole (JEP) (27 : 2008 juin 9-13 : Avignon, FRANCE). . Avignon: LIA. 2008 GHIO, A.; POUCHOULIN, G.; GIOVANNI, A.; FREDOUILLE, C.; TESTON, B.; RÉVIS, J.; BONASTRE, J.-F.; ROBERT, D.; YU, P.; OUAKNINE, M.; GUARELLA, M.-D.; SPEZZA, C.; LEGOU, T.; MARCHAL, A. Approches complémentaires pour l'évaluation des dysphonies : bilan méthodologique et perspectives. Travaux Interdisciplinaires du Laboratoire Parole et Langage d'Aix-en-Provence (TIPA), vol. 26. 2008, p. 33-74. YU P., GARREL R., NICOLLAS R., OUAKNINE M., GIOVANNI A., (2007), "Objective voice analysis in dysphonic patients. New data including non linear measurements", Folia Phoniatrica et Logopaedica, 59:20-30. Lausanne (EPFL). Giovanni A., Yu P., Révis J., Guarella MD., Teston B., Ouaknine M. (2006). "Analyse objective des dysphonies avec l'appareillage EVA. Etat des lieux.", Revue Oto-Rhino-Laryngologie Française, 90, p3 183-192. TESTON, B. L'évaluation instrumentale des dysphonies. Etat actuel et perspectives. In Giovanni A. (ed.) Le bilan d'une dysphonie. ISBN 2-914513-62-3. Marseille: Solal. 2004, p. 105-169. VIALLET, F.; TESTON, B. Objective evaluation of dysphonia: acoustic and aerodynamic methods. Proceedings of European Laryngological Society: Around dysphasia, dysarthria, dysphonia (2003: Toulouse, FRANCE). 2003, p. 53-55. . www.ijeijournal.com Page | 40