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Speech evidence table
General information, not legal advice.
| Field | What to record | Why it changes the review |
|---|---|---|
| Consent | Recording consent, purpose, territory, term, and AI-training language | Consent to record may not cover model training or synthetic voice use |
| Speaker identity | Speaker ID, role, age band where appropriate, and label source | Speaker labels support evaluation but increase identity risk |
| Language | Language, dialect, code-switching, and proficiency context | “Multilingual” is not a substitute for a language manifest |
| Transcript | Human or automatic transcript, version, quality checks, and timestamps | A transcript can be useful while still containing sensitive text or errors |
| Unit | Hours, minutes, utterances, sessions, or files | The unit must match the source and delivery method |
| Recording context | Call, meeting, studio, field, noise, channel, and device | Context helps a reviewer understand use and limitations |
| Rights chain | Employer, client, performer, platform, and music or third-party content | A recorder may not hold every right in a conversation |
Biometric and sensitive-data boundary
General information, not legal advice.
Voice can identify a person even when a transcript has no name. The Illinois Biometric Information Privacy Act Illinois General Assembly, (opens in a new tab) and the FTC voice-cloning policy discussion Federal Trade Commission, (opens in a new tab) are primary context for biometric and identity risk, but neither source clears a private collection.
Masking names from a transcript does not by itself answer voice-identity risk. Consider whether the delivery can use a synthetic or transformed sample, whether speaker labels are necessary, whether a participant can withdraw, and how deletion propagates to derived files. Keep the answer as a documented limitation until counsel confirms the permitted use.
Quality and scarcity without hype
Transcript accuracy, speaker turns, timestamps, clean audio, and consistent metadata make a collection easier to assess. Language scarcity can be a research factor, but it is not a price promise. A June 18, 2026 speech-data buyer guide SpeechData.ai, (opens in a new tab) and a dated multilingual call-center dataset listing Datarade via Internet Archive, (opens in a new tab) are market context only. Record the source date and unit exactly, then state what remains unknown.
Fictional scenario
Imagine a contact center with calls in three languages. The company has a recording notice for service quality, partial transcripts, and a vendor contract that restricts secondary use. A safe first pass labels the calls by language and consent status, excludes the restricted vendor set, and checks whether the remaining recordings contain payment or health details. The owner then prepares a redacted metadata manifest and a small sample only after the intended AI use is reviewed. The output is a rights and quality worksheet, not a claim that all recorded hours are licensable.
Ready-for-review worksheet
Consent status: documented, limited, missing, or counsel review.AI-use language: names training, evaluation, synthetic voice, retrieval, or none.Speaker and biometric review: complete, needed, or out of scope.Transcript: version, QA method, timestamp coverage, and known error classes.Unit: one unit and its definition, with no converted rate unless sourced.Exclusions: third-party rights, health content, payment data, minors, or unknown speakers.Delivery: redacted sample, metadata-only manifest, or administrator-approved export.
Sources
- Illinois General Assembly: Biometric Information Privacy Act (740 ILCS 14) (opens in a new tab)
- Federal Trade Commission: Approaches to Address AI-enabled Voice Cloning (opens in a new tab)
- Rightmark: Trust
- SpeechData.ai: How to Buy Speech Data: The Complete Buyer's Guide (opens in a new tab)
- Datarade via Internet Archive: Global Call Center & Conversational Audio Dataset, Multilingual, Validated, with Demographics + Custom Collection Available (opens in a new tab)