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Seven data types, collected to your requirement.
Structured · Labeled · Annotated. Switch the tab to see each modality, or browse them all below.
Audio & Speech
Speech for ASR and voice AI across languages, accents, and noise levels.
Bespoke audio, collected to your spec.
The sound files your model needs, in the conditions it will face.
Why speech models fail.
Clean audio trains a model that slips where real users speak.
Performs in ideal conditions, slips on real accents, noise, and code-switching.
Holds up where your users actually speak.
The conditions clean audio never sees.
Rwazi collects all of it from real people, so your model meets it in training, before it ships.
See the sample types we collect for cases like yours.
A requested pack contains clips matched to your modality and conditions, with demographic metadata and a naming convention, delivered to your cloud.
Accented and multilingual speech, in real-world noise.
Gated requestCode-switching, spontaneous conversation.
Gated requestStudio-clean, single or multi-speaker.
Gated requestContact-center and noisy-environment audio.
Gated requestWhat we capture, to your spec.
Every dimension is a knob you set on the order, collected to exactly what your model needs.
Two ways to capture, your choice.
We work both ends of the spectrum. You pick the condition your model needs.
Real-world capture
For models that must hold up in production. Accents, background noise, and spontaneous speech, captured where your users actually are.
Studio-grade capture
For models that need precision. Cleaner speech, specific mics, and scripted or semi-scripted prompts, in controlled conditions.
Your users are global. Your training data should be too.
Most speech datasets are built from a handful of major markets, so models stumble elsewhere. Rwazi collects across 190+ countries, in any language with smartphone reach, from native speakers in their own conditions.
- 190+ countries
- 100+ languages
- Regional accents and dialects
- Code-switching
- Real-world or studio
Why teams collect with Rwazi.
Built for the voice AI you are shipping.
Voice assistants, ASR, and conversational AI.
Models stumble on non-standard accents and dialects.
Speech across 100+ languages with regional accents, from native speakers, for ASR and conversational AI datasets.
From your spec to your cloud, in four steps.
Run it as a one-off project or a recurring refresh, weekly or monthly.
How Rwazi compares to other providers.
The same data, captured in the physical world. Here is how that stacks up against the alternatives.
Rwazi plays in physical-world-first AI.
5 million mobile users collecting authentic data from real environments in 190+ countries. Making your models more competitive with real life data.
Quality you set, checked before it ships.
You set the spec. A multi-stage QC team validates every file against your pass-or-reject criteria, with human-in-the-loop review and reports. Every file carries its provenance: who recorded it, where, and when.
- 01You set the pass-or-reject spec
- 02Multi-stage QC team validates every file
- 03Human-in-the-loop review
- 04Provenance recorded per file
- 05Delivered to your cloud
Contact the Rwazi AI Datasets team.
Send us your brief, or book a live demo. We will reply with how we would collect it and a sample to review.
Book a live demo
15 minutes. We walk you through exactly how we collect audio to your spec, in your markets and the conditions your model will face.
Questions teams ask before they buy.
What is audio and speech training data?+
Audio of real people speaking, used to train and fine-tune speech models such as ASR and voice AI. Rwazi collects it to your spec across 190+ countries, real-world or studio.
Do you cover code-switching and noisy environments?+
Yes. We capture mixed-language speech and real-world background noise, or studio-clean when you need it.
Does it include transcription or speaker labels?+
Raw audio is the core. Transcription, timestamps, and speaker labels are available as add-ons.
How is it priced?+
Scoped to your use case. The variables include volume, languages and accents, exclusive versus licensed, and add-ons. Share your requirement and we will scope it.
How does this compare to synthetic or off-the-shelf audio?+
Synthetic and studio audio perform in ideal conditions and slip in production. Rwazi collects to your spec, matching the real conditions your users bring.
Where can I buy voice transcription datasets?+
Share your use case and Rwazi scopes a bespoke speech dataset, with transcription as an add-on layer, licensed or owned outright.
Which languages and accents can you collect?+
Any language with smartphone reach, with regional accents and code-switching. Strongest in English, French, Spanish, Chinese, and Hindi.
What formats and delivery do you support?+
WAV, MP3, and MP4, delivered to your S3, Azure Blob, GCS, or SFTP.
How fast can you deliver?+
Curated sprints run in days; larger or recurring engagements run longer. Run it one-off or as a weekly or monthly refresh.
How do you handle consent and ownership?+
Contributors collect under explicit consent, direct from Rwazi. License it or own it outright, and every file carries its provenance.
What does a delivery look like?+
QC'd files with a consistent naming convention, the format you specify, and demographic metadata at the file level, delivered to your cloud. Raw bulk files are also available.
How do you prepare a speech dataset for machine learning?+
We define the spec with you, collect from real speakers across 190+ countries, run human-in-the-loop QC against your pass-or-reject criteria, then deliver it to your pipeline.