**Introduction** AnnoDIFP (Annotated Data for the Investigation of Facets of Personality) Session Audio and Transcripts was developed by the Linguistic Data Consortium (LDC), the Florida Institute of Technology (FIT), and the University of New Haven (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). 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. **Data** 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. 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. Each session (or session part in the case of multipart sessions) is accompanied by a transcript produced automatically using the Rev.ai speech-to-text service. Speech data is presented as 16 kHz, 16-bit mono-channel FLAC-compressed MS-WAV files. Text data is UTF-8 encoded.

Creator(s)

Christopher Cieri

James Fiumara

Kevin Walker

Mark Liberman

Neville Ryant

Distributor(s)

Linguistic Data Consortium

Right Holder(s)

Linguistic Data Consortium