DOI: 10.35111/e67e-j627
title: Multi-Language Conversational Telephone Speech 2011 -- East Asian

description: <h3>Introduction</h3><br>
<p>Multi-Language Conversational Telephone Speech 2011 -- East Asian was developed by the Linguistic Data Consortium (LDC) and is comprised of approximately 19 hours of telephone speech in two distinct languages of East Asia: Thai and Lao.</p><br>
<p>The data were collected primarily to support research and technology evaluation in automatic language identification, and portions of these telephone calls were used in the NIST 2011 Language Recognition Evaluation (<a href="https://www.nist.gov/itl/iad/mig/2011-language-recognition-evaluation">LRE</a>). LRE 2011 focused on language pair discrimination for 24 languages/dialects, some of which could be considered mutually intelligible or closely related.</p><br>
<p>LDC has also released the following as part of the Multi-Language Conversational Telephone Speech 2011 series:</p><br>
<ul><br>
<li>Slavic (<a href="../../../LDC2016S11">LDC2016S11</a>)</li><br>
<li>Turkish (<a href="../../../LDC2017S09">LDC2017S09</a>)</li><br>
<li>South Asian (<a href="../../../LDC2017S14">LDC2017S14</a>)</li><br>
<li>Central Asian (<a href="../../../LDC2018S03">LDC2018S03</a>)</li><br>
<li>Central European (<a href="../../../LDC2018S08">LDC2018S08</a>)</li><br>
<li>Spanish (<a href="../../../LDC2018S12">LDC2018S12</a>)</li><br>
<li>Arabic (<a href="../../../LDC2019S02">LDC2019S02</a>)</li><br>
<li>English (<a href="../../../LDC2019S06">LDC2019S06</a>)</li><br>
</ul><br>
<h3>Data</h3><br>
<p>Participants were recruited by native speakers who contacted acquaintances in their social network. Those native speakers made one call, up to 15 minutes, to each acquaintance. The data was collected using <a href="https://www.ldc.upenn.edu/about/facilities/human-subjects-collection">LDC's telephone collection infrastructure</a>, comprised of three computer telephony systems. Human auditors labeled calls for callee gender, dialect type and noise. Demographic information about the participants was not collected.</p><br>
<p>All audio data are presented in FLAC-compressed MS-WAV (RIFF) file format (*.flac); when uncompressed, each file is 2 channels, recorded at 8000 samples/second with samples stored as 16-bit signed integers, representing a lossless conversion from the original mu-law sample data as captured digitally from the public telephone network. The following table summarizes the total number of calls, total number of hours of recorded audio, and the total size of compressed data:</p><br>
<table><br>
<tbody><br>
<tr><br>
<td>group</td><br>
<td>lng</td><br>
<td>#calls</td><br>
<td>#hours</td><br>
<td>#MB</td><br>
</tr><br>
<tr><br>
<td>e_asian</td><br>
<td>lao</td><br>
<td>63</td><br>
<td>12.4</td><br>
<td>539</td><br>
</tr><br>
<tr><br>
<td>e_asian</td><br>
<td>tha</td><br>
<td>38</td><br>
<td>6.9</td><br>
<td>354</td><br>
</tr><br>
<tr><br>
<td> </td><br>
<td>totals</td><br>
<td>101</td><br>
<td>19.3</td><br>
<td>893</td><br>
</tr><br>
</tbody><br>
</table><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2019S15.flac">sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2019 Trustees of the University of Pennsylvania