Multi-speaker English dialogue collection format for ASR, diarization, voice-agent evaluation, conversation intelligence, and dialogue model testing.
Natural English Dialogue Sets are built around real spoken interaction: turn-taking, interruption, hesitation, clarification, overlap, repair, topic movement, speaker pacing, and conversational timing. The format is designed for teams evaluating how speech and dialogue models behave on human conversation, not only on clean scripted speech.
Each session is structured around a defined dialogue format such as open discussion, guided prompts, support-style roleplay, interview exchange, task-based conversation, or evaluation dialogue. Recordings can be paired with speaker-labeled transcripts, turn-level timestamps, session metadata, accent fields, channel configuration details, and optional annotation layers for intent, emotion, dialogue acts, overlap, topic shifts, or resolution outcomes.
Structured collection
Dialogue sessions are collected through defined interaction formats: open discussion, guided prompts, support-style exchanges,…
Metadata depth
The dataset format supports speaker-labeled transcript alignment for diarization evaluation, speaker-turn modeling, overlap…
Delivery-ready package
Includes audio quality, speaker clarity, channel structure reviews, plus dataset manifest, CSV catalog, consent status metadata,…
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Share your target language, speaker setup, transcript depth, annotation needs, and evaluation goals. We’ll reply with a technical scope for the collection.
Audio recordings from two or more speakers · Mono, stereo, dual-track, or separated-speaker audio where scoped · Session duration metadata · Recording context metadata
Speaker-labeled transcripts · Timestamped utterances · Turn boundaries · Optional word-level timestamps · Optional confidence fields
Speaker IDs · Speaker role metadata · Language and accent metadata · Region or locale metadata where scoped · Conversation format metadata · Prompt or scenario metadata
Intent labels · Emotion labels · Dialogue-act labels · Interruption markers · Overlap markers · Topic-shift labels · Resolution or outcome labels
Dialogue sessions are collected through defined interaction formats: open discussion, guided prompts, support-style exchanges, interviews, task-based dialogue, or evaluation sessions. Each task defines the speaker setup, conversation objective, topic boundary, and metadata required for delivery.
Audio quality review · Speaker clarity review · Channel structure check · Task match review · Transcript alignment review · Annotation consistency review · Consent status review · Delivery approval
Audio files · Transcript JSON · Transcript CSV where scoped · Speaker/session metadata CSV · Annotation files where scoped · Dataset manifest JSON · CSV file catalog · QA summary · Consent status metadata · Delivery notes
Multilingual dialogue sets with speaker-labeled transcripts, locale metadata, language-span fields, accent or dialect notes, and aligned transcript structures for multilingual ASR and voice-agent evaluation.
Accent-focused speech sets with speaker profile metadata, region fields, prompt categories, transcript alignment, and QA status fields for ASR robustness and voice-agent coverage.
Command-style voice sessions with prompt IDs, intent categories, correction markers, transcript alignment, speaker metadata, and QA fields for instruction-following voice systems.
Role-based support dialogue sets with customer/agent labels, scenario metadata, intent categories, resolution outcomes, transcript structure, and QA fields for support automation evaluation.
Bilingual dialogue sets with language-span markers, speaker labels, timestamped transcripts, code-switch metadata, and aligned language fields for multilingual ASR and translation evaluation.
Ambient audio sets with scene labels, acoustic context metadata, speech screening, device fields, noise-level estimates, and QA status for acoustic scene and robustness evaluation.
