<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.0 20120330//EN" "JATS-archivearticle1.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>The syllable intelligibility in the system of information transmission by speech signals depending on the intensity of acoustic noise</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Yu A Kropotov</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>A A Belov</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>A A Kolpakov</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>A Yu Proskuryakov</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Murom Institute (branch) «Vladimir State University named after Alexander and Nicholay Stoletovs»</institution>
          ,
          <addr-line>Orlovskaya street, 23, Murom, Vladimir Region, Russia, 602264</addr-line>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2019</year>
      </pub-date>
      <fpage>277</fpage>
      <lpage>282</lpage>
      <abstract>
        <p>The paper investigates the effect of the signal-to-noise ratio on syllable intelligibility under the intense influence of external acoustic interference when exchanging voice messages in telecommunication systems of public address systems. The article discusses the effect on the syllable intelligibility of the signal / external acoustic noise ratio, examines the effect of the integral articulation index, the dependence of the perception coefficient of formants on the relative level of formant intensity, the dependence of the formant parameter on the geometric mean frequency of the i-th spectrum of the speech signal. In accordance with the results of studies of the integral articulation index depending on the signal-to-noise ratio, a function of syllable intelligibility depending on the signal-to-noise ratio was obtained, using which it is possible to determine the maximum value of the output signal-to-noise ratio in the audio exchange telecommunications system to obtain a given syllable intelligibility. At the same time, experimentally determined the value of the signal-to-noise ratio in the telecommunications system of audio exchange to obtain a syllable intelligibility of at least 93% for ensure full perception of the transmitted speech information.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. Introduction</title>
      <p>As it is known, the main criterion of efficiency of the system of telecommunication exchange of the
speech information is syllabic legibility S % or the size of an estimation of a speech signal on scale
MOS (Mean Opinion Score) [1].</p>
      <p>
        Telecommunication systems of audio exchange, in particular loudspeaker systems, are considered
to be effective if the transmitted speech information is perceived by the object completely and without
difficulties, the syllable intelligibility in this case is not less than 93% [
        <xref ref-type="bibr" rid="ref1 ref3">1,2,4</xref>
        ] or the MOS score should
be not less than 3,9 points on a five-point scale [
        <xref ref-type="bibr" rid="ref4 ref5">5, 6</xref>
        ].
      </p>
    </sec>
    <sec id="sec-2">
      <title>2. Formulation of the problem</title>
      <p>
        Dependence of syllabic intelligibility in the system of telecommunication exchange of speech
information on the influence of various factors has been studied in a number of works [
        <xref ref-type="bibr" rid="ref2">1,3</xref>
        ]. However,
the information in the known sources [
        <xref ref-type="bibr" rid="ref8 ref9">9, 10</xref>
        ] about the influence of the signal-to-noise ratio on the
syllabic legibility on the side of receiving speech messages for the case of operational-command
telecommunication systems is insufficient, so this article considers the problem of determining the
influence of the signal-to-noise ratio on the syllabic legibility in telecommunication audio exchange
systems.
      </p>
      <p>
        The known results of the studies of the assessment of syllabic legibility by the
instrumentalcalculation method are shown in Fig. 1 [
        <xref ref-type="bibr" rid="ref2">1, 3</xref>
        ].
(1)
(3)
(4)
3. Instrumental-calculation method for estimating the integral articulation index and syllabic
legibility
The value of the integral articulation index R depending on the value of the spectral articulation index
Ri is determined by the expression
      </p>
      <p>N
R = ∑ Ri .</p>
      <p>i=1
The articulation spectral index is calculated by the expression</p>
      <p>Ri = pi · ki , (2)
where pi is formant coefficient, ki is weighting coefficient of the presence of formant speech in the i-th
band.</p>
      <p>
        The coefficient of perception of formant pi is calculated using the expression [
        <xref ref-type="bibr" rid="ref2">3</xref>
        ]
 0,78 + 5,46 ⋅ exp[− 4,3 ⋅10−3 ⋅ (27,3 − Qi )2 ], if Qi ≤ 0;
 1 + 100,1⋅Q
pi = 
1 − 0,78 + 5,46 ⋅ exp[− 4,3 ⋅10−3 ⋅ (27,3 − Qi )2 ], if Qi &gt; 0,
 1 + 100,1⋅Q
where Qi = qi - ΔAi is the relative intensity level of the format.
      </p>
      <p>Or the value of the perception coefficient pi format can be determined by the graph in Figure 2.
The format parameter ΔAi is determined by the graph in Figure 3 or by the expression
200 / f 0,43 − 0.37, если f ≤ 1000 Гц,
∆A( f ) = </p>
      <p>1,37 + 1000 / f 0,69 , если f &gt; 1000 Гц,
where f ср.i = f вi − f нi is average geometric frequency, fнi is lower frequency of the i-th bandwidth
of the speech spectrum, fв is upper frequency of the i-th bandwidth of the spectrum.</p>
      <p>i</p>
      <p>For each i-th (i=1, 2, ... N) frequency band at the average geometric frequency fср.i = fвi − f нi , a
formal parameter ΔAi is determined, characterizing the energy redundancy of discrete components of
the speech signal.</p>
    </sec>
    <sec id="sec-3">
      <title>4. Results of experiments</title>
      <p>Let's take the number of octave bands N=5. Values of the accepted limits by frequency of octave
bands, values of calculated fsr.i and values of formal parameters ΔAi are given in Table 1.</p>
      <p>With the help of expression Qi = qi - ΔAi , we determined the values of intensity levels of format Qi
depending on the signal to noise ratio qi. The calculated values of Qi are summarized in Table 2.</p>
      <p>With the help of expression (3) or according to the diagram in Figure 2, the formatting factor pi is
determined depending on Qi for i-th bands, with different values of signal-to-noise ratio, dB. The
calculated pi values for different qi are summarized in Table 3.</p>
      <p>Qi = qi - ΔAi
qi, дБ
qi = 0 дБ
qi = 3 дБ
qi = 6 дБ
qi = 10 дБ
qi = 20 дБ
qi = 30 дБ</p>
      <p>2,57 ⋅10−8 ⋅ f 2,4 , если 100 &lt; f ≤ 400 Гц;
k( f ) = 
1 −1,074 ⋅ exp(−10−4 ⋅ f 1,18 ), если 400 &lt; f ≤ 10000 Гц;
(5)
or according to the chart in Figure 4.</p>
      <p>The results of calculations of the weighting coefficients of probability of formant speech in the i-th
band are presented in Table 4.</p>
      <p>Calculation of the Ri articulation spectral index is performed by formula (2). Calculations of Ri, at
different values of signal-to-noise ratio are summarized in Table 5.</p>
      <p>Ri = pi·ki
qi = 0 dB
qi = 3 dB
qi = 6 dB
qi = 10 dB
qi = 20 dB
qi = 30 dB</p>
      <p>According to the results of calculations of the spectral articulation index Ri, summarized in Table 5,
it became possible to calculate the integral articulation index depending on the signal-to-noise ratio.
The results of the calculation of the integral articulation index made it possible to find the values of
syllabic legibility depending on the signal-to-noise ratio, which are summarized in Table 6.
5.</p>
      <p>The graph of the syllable intelligibility function S from the signal-to-noise ratio is shown in Figure
1</p>
      <p>2
1 – english speech
2 – russian speech
S,%
90
80
70
60
50
40
30
20
10
0
3
6
10
20
30 q , dB</p>
    </sec>
    <sec id="sec-4">
      <title>5. Conclusions</title>
      <p>
        As can be seen from the graphs in Figure 5, the syllable intelligibility of the voice messaging
telecommunications system is ensured by S≥93% for signal/noise ratio q≥20 dB [
        <xref ref-type="bibr" rid="ref6 ref7">7, 8</xref>
        ]. Thus, the
dependence of syllabic intelligibility on signal-to-noise ratio, which is important for the practice of
telecommunication systems, is obtained. It shows that for effective transmission of speech information
by the command and control system of telecommunications, for obtaining, respectively, syllabic
intelligibility of S≥93%, in the system for transmission of speech messages, it is necessary to provide
signal-to-noise ratio q≥20 dB on the receiving side of messages.
      </p>
    </sec>
    <sec id="sec-5">
      <title>6. References</title>
      <p>[1] Sapozhkov M A 1962 Speech signal in cybernetics and communications (Moscow: Svyazizdat)
p 452</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          [2]
          <string-name>
            <surname>GOST</surname>
            <given-names>R</given-names>
          </string-name>
          50840
          <article-title>-95 Speech transmission via communication channels</article-title>
          .
          <article-title>Methods to assess quality, legibility</article-title>
          and recognizability
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          [3]
          <string-name>
            <surname>Zheleznyak</surname>
            <given-names>V K</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Makarov Y K and Khoreev A A 2000</surname>
          </string-name>
          <article-title>Some methodical approaches toevaluation of efficiency of speech information protection</article-title>
          <source>Special technique</source>
          <volume>4</volume>
          <fpage>39</fpage>
          -
          <lpage>45</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          [4]
          <string-name>
            <surname>Cohen</surname>
            <given-names>I</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Benesty</surname>
            <given-names>J</given-names>
          </string-name>
          and
          <string-name>
            <surname>Gannot</surname>
            <given-names>S 2010</given-names>
          </string-name>
          <article-title>Speech processing in modern communication</article-title>
          (Berlin, Heidelberg: Springer) p
          <fpage>342</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          [5]
          <string-name>
            <surname>Hansler</surname>
            <given-names>E</given-names>
          </string-name>
          and
          <string-name>
            <surname>Schmidt</surname>
            <given-names>G 2006</given-names>
          </string-name>
          <article-title>Topics in acoustic echo and noise control: Selected methods for the cancelation of acoustic echoes, the reduction of background noise, and speech processing</article-title>
          (Berlin, Heidelberg: Springer) p
          <fpage>642</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          [6]
          <string-name>
            <surname>Kahrs</surname>
            <given-names>M</given-names>
          </string-name>
          and
          <article-title>Brandenburg K 2002 Applications of digital signal processing to audio and acoustics</article-title>
          (New York: Kluwer Academic Publisher) p
          <fpage>572</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          [7]
          <string-name>
            <surname>Kropotov</surname>
            <given-names>Y A</given-names>
          </string-name>
          and
          <string-name>
            <surname>Belov</surname>
            <given-names>A A</given-names>
          </string-name>
          <year>2016</year>
          <article-title>Application method of barrier functions in the problem of estimating the probability density of the parameterized approximations 13th</article-title>
          <source>International Scientific-Technical Conference on Actual Problems of Electronic Instrument Engineering</source>
          <volume>69</volume>
          - 72
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          [8]
          <string-name>
            <surname>Kolpakov</surname>
            <given-names>A A</given-names>
          </string-name>
          and
          <string-name>
            <surname>Kropotov</surname>
            <given-names>Y A</given-names>
          </string-name>
          <year>2017</year>
          <article-title>Advanced mixing audio streams for heterogeneous computer systems in</article-title>
          <source>telecommunications CEUR Workshop Proceedings</source>
          <volume>1902</volume>
          <fpage>32</fpage>
          -
          <lpage>36</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          [9]
          <string-name>
            <surname>Ryabenkyi</surname>
            <given-names>V S</given-names>
          </string-name>
          <year>2012</year>
          <article-title>Mathematical model of the external noise suppression devices in the subarea of space</article-title>
          <source>Mathematical modeling</source>
          <volume>24</volume>
          (
          <issue>8</issue>
          )
          <fpage>3</fpage>
          -
          <lpage>31</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          [10]
          <string-name>
            <surname>McAulay R and Malpass M 1980</surname>
          </string-name>
          <article-title>Speech enhancement using a soft-decision noise suppression filter IEEE Trans, on Acoustics, Speech, and</article-title>
          <source>Signal Processing</source>
          <volume>28</volume>
          (
          <issue>2</issue>
          )
          <fpage>137</fpage>
          -
          <lpage>145</lpage>
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          [11]
          <string-name>
            <surname>Kropotov</surname>
            <given-names>Y A</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Belov</surname>
            <given-names>A A</given-names>
          </string-name>
          and
          <string-name>
            <surname>Proskuryakov</surname>
            <given-names>A Y</given-names>
          </string-name>
          <year>2018</year>
          <article-title>Method for forecasting changes in time series parameters in digital information management systems</article-title>
          <source>Computer Optics</source>
          <volume>42</volume>
          (
          <issue>6</issue>
          )
          <fpage>1093</fpage>
          -
          <lpage>1100</lpage>
          DOI: 10.18287/
          <fpage>2412</fpage>
          -6179-2018-42-6-
          <fpage>1093</fpage>
          -1100
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>