Physical audio data for speech and voice models
World Audio designs and runs consented, capture-authentic audio programs for ASR, speaker diarization, TTS, and speech-to-speech systems—built around the conditions where your model fails.
Founding design-partner program · working company concept
A So we ship on Thurs—B Thursday, yes.
Recruit by language, accent, age band, vocal range, speaking style, and domain expertise. Consent and usage rights travel with every recording.
The data gap
Voice systems leave the benchmark and meet microphones, rooms, people, devices, latency, and competing sound. That is where transcript accuracy bends, speaker identity collapses, and synthetic voices stop feeling responsive.
The next model gain may not need more audio. It may need the right physical audio.
What we collect for
Each program changes with the target behavior. Recruitment, acoustic design, interaction shape, annotation, and acceptance criteria follow the model—not a generic collection template.
Scripted and spontaneous speech across accents, devices, distances, noise bands, code-switching, domain vocabulary, and long-form sessions.
Natural multi-speaker exchanges with interruption, overlap, backchannels, speaker movement, channel-separated references, and adjudicated turns.
Consented studio and in-context speech spanning prosody, emotion, pace, pronunciation, vocal effort, expressive reads, and directed variation.
Full-duplex conversations with latency, repair, interruption, role, intent, turn-taking, and paired audio–text artifacts for conversational models.
The physical signal chain
Every step preserves the link between who spoke, what happened in the room, how the audio was recorded, how it was labeled, and what the customer is allowed to do with it.
Bring us a failure caseBring a weak accent cohort, a diarization break, an unnatural voice behavior, or a target environment your current corpus does not cover.
We define speakers, settings, hardware, prompts, interaction shape, metadata, rights, acceptance tests, and the delivery schema.
Facilitated sessions preserve device, room, channel, timing, noise, and participant provenance at the source.
Audio and annotations pass automated checks, human review, language QA, and targeted re-runs before they enter the accepted set.
Receive versioned audio, manifests, alignments, speaker and condition metadata, consent records, and a documented acceptance report.
What a deliverable looks like
A dataset is not a folder of WAV files. It is audio plus the evidence needed to reproduce selection, filter failure, evaluate coverage, and defend the rights chain.
Illustrative pilot structure · not a completed World Audio dataset
audio/FLAC · 48 kHz · 24-bitraw + accepted channelssegments.jsonlword + turn alignedASR / diarization targetsconditions.parquetroom · device · SNRcoverage and slicingparticipants/redacted identitiesconsent and usage scopedata_card.mdversioned reportlimits, QC, known gapsWhere the signal happens
Paired and group dialogue with interruption, repair, backchannels, emotion, role, and real turn timing.
Phones, headsets, far-field arrays, embedded microphones, codecs, echo paths, and network degradation.
Homes, offices, vehicles, public spaces, industrial settings, controlled rooms, and measured noise playback.
Prosody, phonetic coverage, emotion, pace, effort, pronunciation, and repeatable controlled variation.
Rights are part of the data
Recruitment, identity checks, intended model use, voice rights, recording conditions, compensation, retention, and withdrawal rules are designed before the first session.
Before a pilot
The first offer is a custom pilot built around a model gap. Reusable dataset modules can follow once rights, demand, and quality thresholds are proven.
Start with one gap
Describe the target behavior, speakers, and physical conditions. We will turn it into a pilot-shaped collection brief.