French Full-Duplex Conversational Dataset
MarketplaceNaturalistic French conversations between native speakers, captured in full-duplex stereo with overlapping speech and authentic turn-taking.
Overview
Naturalistic, two-speaker French conversations captured at studio quality in full-duplex stereo. Pairs of native French speakers from metropolitan France, Belgium, and French-speaking parts of Canada discuss everyday topics for the full duration of the session — no read scripts, no scene cuts. Each recording preserves real overlapping speech, backchannels, hesitations, and code-switching, so downstream models train on the way French actually sounds in the wild. Every clip is collected from paid contributors with explicit consent, scene-level provenance, and metadata for speaker demographics, dialect, and acoustic environment.
Key highlights
- 01
Hexagonal France, Belgian, and Québécois pairings with per-speaker dialect tags so models can learn regional pronunciation drift.
- 02
Verlan, register switches between formal vous and informal tu, and Parisian abbreviations ("chui", "ouais") preserved as-spoken.
- 03
Café-style conversational cadence — interruptions, agreement particles ("voilà", "bah"), and rhetorical questions captured intact.
- 04
Regional vocabulary and pronunciation differences across Lyon, Marseille, Brussels, and Montréal annotated in the speaker metadata.
- 05
Disfluencies — filled pauses (uh, um, hmm), false starts, self-repairs, hesitations, laughter, sighs, breath, and throat clears — are preserved with utterance-level timestamps rather than normalised away, so models can learn from them or filter them out as a first-class signal.
Technical specifications
Coverage
Hundreds of paired sessions from native French speakers across France, Belgium, and Canada — coverage extends to bespoke dialects, age groups, and topical targets on request.
Capture specs
Stereo full-duplex audio at 48 kHz / 24-bit per channel from studio-grade microphones, with per-speaker channel isolation, calibrated noise floor, and continuous capture for the full lifespan of each session — not cherry-picked moments.
Annotations
Every session ships with rich speaker / contributor metadata (age, gender, region, dialect, native language, acoustic environment) plus an utterance-level annotation layer: emotion tags (joy, frustration, neutral, surprise, sadness, anger, amusement, empathy, and more), topic tags spanning everyday domains (work, family, sports, travel, health, finance, technology, food, pop culture, politics, education), intent labels (question, agreement, backchannel, hedge, interruption, repair, opinion), turn-taking markers (overlap onset/offset, gap, hold, yield), and prosody cues (pitch contour, stress, laughter, sighs, hesitation, code-switch boundaries). Custom annotation schemas — domain-specific intents, fine-grained emotion taxonomies, named-entity spans, sentiment scoring, or any task-specific labels — are available on request.
Use cases
- Full-duplex conversational AI training and evaluation
- Speaker diarization and French ASR / TTS modelling
- Turn-taking, backchannel, and overlap-handling research
- Emotion-aware and intent-aware voice agent fine-tuning
- Voice agent benchmarks for natural, multi-party conversation
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