How these notes are written

Structure

Most notes follow the same shape: what the thing is, what it does well, where it fails, how to measure that in your own operation, and what to do about it.

The failure sections are not optional. A description of speech analytics that omits transcription error and the accuracy disparity between speakers describes a product that does not exist.

Measurement over assertion

Where a note says something can be measured, it says how, on your own data, in terms a small team can execute. Vendor figures are treated as claims to be tested rather than as facts.

Several notes are entirely procedures for measuring something the industry usually asserts: word error rate by speaker group, category precision, inter-rater agreement, summary fidelity, redaction leakage.

The uncomfortable material

Three findings recur and each has its own note.

Speech recognition performs unevenly across speakers, which makes automated scoring unequal unless measured and mitigated.

Emotion inference rests on contested science and is increasingly restricted in employment contexts.

Small samples cannot characterise individuals, which undermines most agent-level QA scoring as it is practised.

These are stated because programmes built without them produce unfair outcomes for the people being measured.

Legal material

Descriptions of recording consent, biometric regulation, employee monitoring and data protection are general and jurisdiction-dependent. They are not legal advice and the notes say so. Take advice for your jurisdictions before deploying anything described here.

Commercial position

Software guides use public product information and a repeatable pilot framework. There are no sponsored placements or affiliate links, and inclusion is not an endorsement. Vendor claims are treated as statements to verify on the reader's own data.