Recognize natural speech
Specify regional language coverage, accents, code-switching and acoustic conditions. Assess transcript conventions against your recognition task.
FIUND / Speech & voice AI
License conversations and language-specific recordings for speech recognition, speaker understanding and conversational AI. Define the speaker mix, recording conditions and evaluation task before selecting the data.
Conversation context
Boundaries · roles · overlap
Language · timestamps · text
Model tasks
Specify regional language coverage, accents, code-switching and acoustic conditions. Assess transcript conventions against your recognition task.
Look for useful speaker separation, interruptions and overlapping conversation. Agree the timestamp and speaker-label conventions needed for your evaluation.
Use connected exchanges to examine turn-taking and spoken context. Define the setting and participants that matter for your model.
Explore the source formats and context that could support your task. Access and suitability are confirmed for each proposed project.
Scope before scale
Countries, varieties, speaker characteristics, recording environments and channel conditions.
Source audio, track separation, sampling rate, transcript availability and any additional annotation work.
Representative samples, intended use, acceptance criteria and permitted recipients.
Sample review
Review the published collection scope, then request a sample for your intended evaluation. Other sources and annotations are scoped separately.
They depend on the selected collection. We confirm existing annotations and identify any preparation required before agreeing scope and pricing.
Yes. Specify the region, recording setting and speaker mix. Suitable sources, permissions and timing are confirmed against your brief.
The standard licence does not authorize cloning an identifiable person’s voice or likeness. Permitted AI uses are defined in the agreement.