The decision
Before using our newly adapted audio IAT platform to evaluate short-form sonic assets, we needed to establish that it could reliably distinguish between sounds with clearly positive and negative emotional associations.
The evidence
Eight familiar, naturally occurring sounds were tested, from baby laughter and birdsong to security alarms and screams of pain. Every sound produced an implicit response consistent with its expected positive or negative association. The results also replicated an earlier study using the same sounds on a different implicit testing platform.
The outcome
The validation established confidence in the platform’s ability to capture implicit emotional responses to audio and produced a reference continuum, with baby laughter at the 100th percentile and a scream of pain at the 1st.
- Methodology
- Audio Implicit Association Testing
- Validation stimuli
- 8 everyday sounds
- Strongest positive response
- Baby laughter, +138 ms
- Strongest negative response
- Pain scream, −40 ms
- Cross-platform validation
- Results replicated; face validity established
The full story
Before asking whether a sonic logo makes a brand more emotionally appealing, we needed to establish something more fundamental. Could our testing platform accurately measure the emotional associations people have with sound? Working with RIWI, we adapted its Implicit Association Testing platform to accommodate audio, then put it through a straightforward validation exercise. We selected eight familiar sounds with reasonably predictable emotional associations, ranging from baby laughter, applause, and birdsong to car crashes and screams of pain. If the methodology was working as intended, positively associated sounds should produce positive Emotional Appeal scores, while negatively associated sounds should produce negative scores.
That is precisely what happened. Baby laughter registered the strongest positive response, a net response-time difference of +138 ms, an Emotional Appeal Index of 121 and the 100th percentile of our reference distribution. Applause (+80 ms) and birdsong (+71 ms) also scored strongly, while security alarms (−21 ms), car crashes (−25 ms), and screams of pain (−40 ms) occupied the negative end of the continuum. The pattern replicated results from an earlier study conducted using the same sounds on a different implicit testing platform. Together, these findings provided face-validity evidence for our adaptation of the methodology and established a useful reference for interpreting subsequent audio research. They also provided a striking benchmark: even the most carefully engineered sonic identities have yet to surpass the implicit emotional appeal of a baby’s laugh.