Citable proof
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Trainjust’s audio corpus includes dual-channel call-center audio across real industry contexts and multiple languages.
Dual-Channel Audio
Dual-channel audio records two speakers or sides of a conversation on separate tracks, such as an agent and a customer in a call center. This separation makes it easier to train ASR, speaker diarization, conversation analytics, and voice AI systems.
Speech AI
Why Dual Channels Matter
When speakers are separated, models can learn turn-taking, speaker roles, interruptions, and customer-agent behavior more reliably than from mixed single-channel audio.
- Cleaner diarization labels
- Better role-aware transcription
- More useful conversation analytics
Common AI Use Cases
Dual-channel audio is valuable for speech recognition, customer-support AI, QA automation, voice agents, and multilingual speech analytics.
- ASR fine-tuning
- Speaker diarization
- Conversational voice AI