Indonesian Full-Duplex Conversation Dataset
MarketplaceBahasa Indonesia conversations between native speakers, captured in full-duplex stereo across Java, Sumatra, and Sulawesi.
Overview
Naturalistic, two-speaker Bahasa Indonesia conversations captured at studio quality in full-duplex stereo. Pairs of native Bahasa Indonesia speakers from Java, Sumatra, Sulawesi, and other Indonesian provinces 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 Bahasa Indonesia 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
Standard Bahasa speakers paired with Javanese, Sundanese, and Sumatran code-switching captured at the utterance level.
- 02
Casual Jakarta slang and colloquial particles (-lah, -dong, -sih, -kok) preserved across speaker turns.
- 03
Religious greetings, family-style honorifics, and Arabic loanwords from Muslim contributors tagged in the metadata layer.
- 04
Regional dialect variation across Java, Sumatra, Sulawesi, and Bali balanced in the contributor pool.
Technical specifications
Coverage
Hundreds of paired sessions from native Bahasa Indonesia speakers across Indonesia — 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
Speaker / expert metadata shipped with every session: age, gender, region, dialect, native language, and acoustic environment. Annotations available at request.
Use cases
- Full-duplex conversational AI training and evaluation
- Speaker diarization and Bahasa Indonesia ASR / TTS modelling
- Turn-taking, backchannel, and overlap-handling research
- Voice agent benchmarks for natural, multi-party conversation
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