DOI: 10.35111/kbj5-9864
title: AnnoDIFP Session Audio and Transcripts

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<h1>AnnoDIFP Session Audio and Transcripts</h1>
<h3 class="subtitle">LDC2025S06</h3>

<h3>Introduction</h3>
<p> AnnoDIFP (Annotated Data for the Investigation of Facets of Personality) Session Audio and Transcripts
    was developed by the Linguistic Data Consortium (LDC), the <a href="https://www.fit.edu/">Florida Institute of
    Technology </a> (FIT), and the <a href="https://www.newhaven.edu/index.php">University of New Haven</a> (UNH) to support  algorithm development for predicting personality traits. It contains 438.34 hours of English audio and transcripts from in-person interviews of 366 participants  paired with scores from two self-reported personality
    assessments, HEXACO Personality Inventory (Revised) (HEXACO-PI-R) and
    Short Dark Triad (SD3).
</p>
<p>Survey and behavioral data were collected in three phases. Phase 1 consisted of online questionnaires. Selected participants were invited to participate in Phase 2a, collecting behavioral and linguistic data in a laboratory setting. In Phase 2b, participants engaged in a telephone speech collection by calling other particpants. This release covers the activities in Phase 2a. </p>
<h3>Data</h3>
<p>In-person interviews were recorded at LDC, FIT and UNH. In each session, the participant and interviewer sat in separate sound-isolated rooms with communication between them supplied by audio/video hardware. Sessions consisted of the following tasks: rapport building, a YouTube task, a map task, and a business task. Further details on collection methodology and session tasks are contained in the documentation accompanying this release.</p>
<p>There were a total of 386 participants in Phase 2a. This corpus contains audio data and transcripts from 301 participants and transcripts only for 65 participants. Recordings for 20 participants were not usable. 
</p>
<p>Each session (or session part in the case of multipart sessions) is accompanied
by a transcript produced automatically using the <a href="https://www.rev.ai/">Rev.ai</a>
speech-to-text service.</p>

<p>
	Speech data is presented as 16 kHz, 16-bit mono-channel FLAC-compressed MS-WAV files.
 Text data is UTF-8 encoded.</p>


<h3>Updates</h3>   

    <p>
		Additional information, updates, bug fixes may be available in the LDC
   	catalog entry for this corpus at <a
    	href="http://catalog.ldc.upenn.edu/LDC2025S06">LDC2025S06</a>.
    </p>

    
<h3>Content Copyright</h3>
<p>Portions © 2025 Trustees of the University of Pennsylvania</p>
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