Technical Specifications
Production-ready delivery formats, audio standards, and dataset metadata conventions.
Detailed specs vary by project. A finalized spec sheet is provided during scoping.
Quick Spec Summary
| Audio Formats | WAV, FLAC |
| Sample Rates | 16 kHz, 44.1 kHz, 48 kHz |
| Bit Depth | 16-bit, 24-bit |
| Channel Config | Mono (stereo on request) |
| Metadata Format | Structured JSON manifests |
| Delivery Package | Archive with folder structure defined during scoping |
Audio Standards
Recording constraints: Device constraints enforced at capture time, sample rate validation before submission, noise floor checks applied automatically, invalid audio rejected before entering pipeline.
Validation checks: Sample rate matches project specification, environment noise floor within acceptable threshold, no clipping or distortion detected, audio duration within expected range.
Specific thresholds (SNR, noise floor dB, environment requirements) are defined per project during technical scoping.
Annotation and Segmentation Conventions
Segmentation approach: Recordings are segmented at the utterance level by default. File-level segmentation or alternative approaches are available on request and specified during project scoping.
Transcript and label formats: Transcripts are delivered as verbatim or normalized text depending on project requirements. Label formats are aligned with common training pipeline conventions.
Manifest schema: Datasets include structured JSON manifests with fields such as recording_id, speaker_id, transcript, duration_ms, sample_rate, format, language, region, consent_reference, and qa_status.
Complete schema documentation is provided during scoping. Additional fields available on request.
Quality Assurance Outputs
Automated validation: Quality threshold enforcement (SNR, clipping, silence detection), synthetic artifact detection, technical specification compliance check, automatic rejection of non-conforming recordings.
Human QA stage: Every recording undergoes human review—100% of recordings are reviewed before acceptance. Includes linguistic correctness review, naturalness assessment, script adherence verification, and per-recording acceptance decision.
Dataset-level QA: Coverage balance verification, speaker distribution analysis, label integrity check, and final acceptance review before delivery.
Delivery and Handoff
Delivery method: Delivery methods are defined during scoping and may include secure transfer, cloud storage handoff, or other enterprise-compatible mechanisms.
Versioning and iterations: Iteration cycles, revision policies, and version control are defined during project scoping and are contract-bound.
Handoff procedures, acceptance criteria, and post-delivery support are documented in the project agreement.
Integration Notes
YPAI datasets are delivered in formats compatible with standard ML training pipelines. This page does not document APIs—delivery is file-based and designed for offline training workflows.
Integration overview: Datasets delivered in WAV/FLAC with structured JSON manifests, folder structure and naming conventions documented per project, compatible with common ASR/TTS training frameworks. Integration spec available on request during scoping.
What This Page Covers
This page describes: Typical formats and conventions, standard QA process outputs, and delivery and integration overview.
Not covered here: Project-specific specifications (finalized during scoping), pricing and commercial terms, open datasets, marketplace, or crowdsourcing.
Procurement appendices, legal terms, and DPA documentation are linked from the main Speech Data page or provided during enterprise consultation.
Frequently Asked Questions
What audio formats does YPAI support for speech datasets?
YPAI delivers speech datasets in WAV and FLAC formats. The specific format is defined during project scoping based on your pipeline requirements.
What sample rates are available?
Standard sample rates include 16 kHz, 44.1 kHz, and 48 kHz. The appropriate sample rate for your project is determined during technical scoping based on your use case and training requirements.
How is audio quality validated?
YPAI applies both automated validation (SNR checks, clipping detection, technical compliance) and mandatory human QA for every recording. 100% of recordings are human-reviewed before acceptance—this is not a sampled process.
What metadata is included with delivered datasets?
Datasets include structured JSON manifests containing fields such as recording_id, speaker_id, transcript, duration_ms, sample_rate, format, language, region, consent_reference, and qa_status. Additional fields are available on request.
Can I request stereo recordings instead of mono?
Yes. The default configuration is mono, but stereo recordings are available on request and can be specified during project scoping.
How are transcripts formatted?
Transcripts are delivered as verbatim or normalized text depending on project requirements. The specific format and conventions are documented during scoping.
What segmentation approach is used?
Recordings are segmented at the utterance level by default. File-level segmentation or alternative approaches are available on request and specified during project scoping.
How is data delivered?
Delivery methods are defined during scoping and may include secure transfer, cloud storage handoff, or other enterprise-compatible mechanisms. Specific options are documented in the project agreement.
Are YPAI datasets compatible with standard ML frameworks?
Yes. Datasets are delivered in formats compatible with standard ML training pipelines, including common ASR and TTS training frameworks. Integration specifications are available on request during scoping.
What QA documentation is provided with delivered datasets?
Delivered datasets include QA reports documenting validation results, coverage balance verification, speaker distribution analysis, and label integrity checks. Specific documentation scope is defined during project scoping.
Can specifications be customized for my project?
Yes. Technical specifications are defined per engagement and finalized during scoping. YPAI works with your team to define project-specific requirements, thresholds, and deliverables.
Is there an API for accessing datasets?
YPAI datasets are delivered as file-based packages designed for offline training workflows. This is not an API-based or streaming service.
Next Step
Start a scoped, confidential discussion with our data team to define project-specific technical specifications.