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<!doctype html>
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<title>Mysolution - Lab AI Japan-Machine Learning</title>
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<h2>Mysolution-Lab.Japan</h2>
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<li><a href="#home">About us</a></li>
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<h2>TheTechnical NarrativeofOSP for UPs-OSAKA</h2>
<p> </p>
<p style="font-size:120%;">This version of OSP is customized for UP, an English School in Osaka-Japan.
This version can measure the <span style="color:orange;">“Reading Rate” </span>of a speaker and compare it
with the <span style="color:orange;">average rate </span> of non-native and native speakers.</p>
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<h2>Introduction</h2>
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<h3 class="text-uppercase colorstext">1- In this narrative, we explain how Mysol’s OSP-Reading-Rate works and look at the factors which influence the users’ Reading-Rate.</h3>
<h3 class="text-uppercase colorstext">2- The chief goal is to deploy Mysol’s OSP-Speaking-Rate in three phases, by which we measure the users’ Speaking-Rate, a critical component of the language delivery.</h3>
<h3 class="text-uppercase colorstext">3- In phase-1, we focus on measuring only five types of suprasegmental features in utterances.</h3>
<UL>
<LI style="color:orange; font-size:120%;">* Inappropriate pausing (IP),
<LI style="color:orange; font-size:120%;">* Absence of pausing (AP),
<LI style="color:orange; font-size:120%;">* Absence of CV linking (AL),
<LI style="color:orange; font-size:120%;">* Inappropriate lexical stress (ILS),
<LI style="color:orange; font-size:120%;">* Inappropriate intonation (II).
</UL>
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<h3 class="text-uppercase colorstext">OSP-Reading Rate </h3>
<p>The scientific way to measure one’s Reading/Speaking rate is in syllables per second. </p>
<p>OSP’s estimate of the <span style="color:orange;">“Reading Rate”</span> is obtained by timing the user while reading a selection of text with a known syllables count.</p>
<p>OSP evaluates the competency of the user by employing mathematical formulas and ETS’s<span style="color:orange;"> independent speaking rubrics and philosophy </span>(Educational Testing Service-USA).</p>
<p>OSP went through a<span style="color:orange;"> Machine learning </span>session, with an audio dataset of non-native and native English speakers. These audios ranged from
just 2 minutes in length to just under 5 minutes. Speakers' topics were widely variable.</p>
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<h3 class="text-uppercase">Scope and limitations </h3>
<h4 class="text-uppercase">Note, this is not the ”Speaking Rate”. Even if the user reads out loud,
it’s not the same thing as a speaking rate.</h4>
<h4 class="text-uppercase">The best way to determine the user’s speaking rate
is to time the user’s delivering a free speech. </h4>
<h4 class="text-uppercase">All the annotations that will been analyzed by the current OSP-Reading are based on
the mentioned rubrics and the non-native English speaker audios.
We do not claim that these are 100% accurate or the only way
the speech can be analyzed. We will upgrade the OSP algorithm.
Your comments and feedback are most welcome.
Please feel free to contact us and let us know your thoughts about the corpus.</h4>
</div>
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<h2>How to make high quality recordings</h2>
<h3 style="color: black">Step 1. Find a quiet place for recording Make sure to turn off all
background machinery and electronic appliances, such as your mobile phones or TV set.</h3>
<h3 style="color: black">Step 2. Set up your recording equipment
Plug in and test your microphone. Please do not put the microphone too close to
your mouth(10-12 inches from the speaker is preferred)to avoid “p pops".</h3>
<h3 style="color: black"> Step 3. Adjust the recording settings Before starting your recording,
you must be certain that your machine sound recorder
will record at DVD quality mono settings (44.10 kHz., 24-bit, mono).</h3>
</div>
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<img src="assets/images/service1.png" alt="" />
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<p class="btn btn-larg">For each session of the student training,
we recommend teachers select five types of sentences:
wh- questions, declarative sentences, yes-no questions,
tag questions, closed-choice alternative questions </p>
</div>
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<p class="btn btn-larg">which can help eliminate or counterbalance
the effects of different sentence types on suprasegmental
features produced by learners and reveal the segmental features
in different sentence types. </p>
</div>
</div>
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<p class="btn btn-larg">Suggested pausing<br/>
Suggested intonation<br/>
Suggested linking<br/>
Suggested lexical stress for multisyllabic words</p>
</div>
</div>
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<h2>Contact us</h2>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<h3 class="text-uppercase">Office</h3>
<span>HASEGAWA Bldg 5F</span>
<span>Izumi Higashi-ku Nagoya City 1-14-3 .</span>
<span> Japan</span>
<p> +81-52-212-8888
<p class="text-lowercase" style="color:aqua;">[email protected]</p>
<p> </p>
<p> Mysol 久屋大通校 〒461-0001 愛知県名古屋市東区Higashi-ku, Izumi, 1 Chome−14, 泉1丁目14−3 ハセガワビル</p>
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<p class=" wow fadeInRight animated" data-wow-duration="1s">Made with <i class="fa fa-cog fa-spin"></i>
by <a href="https://github.com/Shahabks">Mysolution Lab</a> 2018. All Rights Reserved</p>
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