Speech analytics and quality · L1 · 15 min
Transcription of a recording
Learn in five minutes
- Wikipedia defines speech analytics as analyzing recorded calls to gather customer information.
- That page says it includes automatic speech recognition and is known for setting the topic against the emotional character of the speech.
- It says applications can spot keywords on live audio or as a later pass on a recording.
- It says word error rate compares a transcription with a reference, and that word error rate is not always what a search user needs.
- A transcript is text. It is not proof of the label someone adds afterward.
Keep the audio, the transcript, and the label in three boxes. A fluent transcript can still contain the wrong word.
Visual
Three boxes
- Box 1: the recording you are allowed to hear.
- Box 2: the transcript.
- Box 3: empty, until a later room, for a sentiment or quality label.
- If you have no reference transcript, do not invent a word error rate.
Quiz
Ecosystem
- Transcript
- Text from speech. It still needs a check against audio you are allowed to hear.
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
- Speech recognition — Wikipedia wikipedia last checked 2026-10