The stricter the quality gate, the more monotone readings survive — Selection bias caused by verification

When automatically generating a learning corpus with emotional expressions, all of it ended up being monotone. The cause was the quality gate itself; Whisper verification tends to reject emotionally charged audio and pass flatter takes more easily. What happens when filtering and ranking are done using the same metrics?