Speech analytics and quality · L3 · 20 min
Pitfalls
Learn in five minutes
- A fluent transcript can still have the wrong word. Check it against audio you are allowed to hear.
- Wikipedia's sentiment page lists metaphor, differences in writing, and context as reasons a class can change.
- Precision and recall, on the speech-analytics page, answer different questions. Report which one you computed.
- A redaction that deletes the name and keeps a unique account number has not removed the identifier.
- Do not paste a real customer's recording into this lab.
Each pitfall has a check you can do on a toy line. None of them is fixed by a more confident sentence.
Visual
Four checks
- Transcript: compare one word with the audio, or write 'no audio, no word-error claim.'
- Sentiment: write the context that could flip the label.
- Search: write whether you computed precision or recall.
- Redaction: search the line for a number you left behind.
Quiz
Ecosystem
- Pitfall
- A failure mode named by a source. It is not solved by a fluent sentence.
Sisters: Automatic speech recognition, Sentiment analysis, Quality rubrics, Personal data.
The live voice pipeline answers the person. Analytics reads a recording later. Keep those clocks apart.
A later review can add a rubric you wrote. It cannot borrow a customer's tape.
Config
- Write the goal in one sentence.
- Name the input and the allowed output.
- Save the trace next to the result.
Troubleshooting
- The answer looks fluent and is wrong. Check whether a source passage actually contains the claim.
- The loop never stops. Set a step cap and stop when the tool result repeats.
Sources and go deeper
- Speech analytics — Wikipedia wikipedia last checked 2026-10
- Sentiment analysis — Wikipedia wikipedia last checked 2026-10
- Personal data — Wikipedia wikipedia The page title is Personal data. last checked 2026-10