Research study · AI voice detection

Can you learn to hear the difference?

You'll listen to short voice clips and decide whether each is a real human or an AI. Partway through, half of participants get a short lesson on what to listen for. Everyone is tested the same way at the end, including on an AI model no one trains on.

Before you start

This is a research study. Your responses are recorded anonymously (no name, no email). It takes about 15 minutes. You can stop anytime. Please use headphones in a quiet room if you can.

Consent language and any parental-permission flow go here, finalized to match IRB approval before real data collection.

This study is publicly pre-registered on the Open Science Framework — osf.io/h8tpr. Our hypotheses, analysis plan, and power analysis were posted before any data was collected.

Before we start

A few quick things

This study is about hearing small differences in voices, so a few conditions really matter for the data to be usable.

I'm using headphones or earbuds (not laptop speakers). I'm in a reasonably quiet place. I can focus for about 15 minutes without interruption.

Headphone check

Quick sound test

You'll hear three quiet tones in a row. One of them is softer than the other two. This test only works over headphones — it's how we confirm the audio is set up right.

Trial 1 of 3

Baseline1 / 12

Clip 1

Human or AI, and how sure are you?

Play the clip to unlock your answer.

No feedback during tests — just your best judgment.

Phase 2 of 4

Now, some training.

You'll practice on real-vs-AI clips with feedback.

Cue 1 of 4Card 1 of 4

Cue

Practice

Clip 1

Human or AI, and how sure are you?

Correct

Complete

Thank you.

Here's how your ear did across the study. The number that matters most is the last one: how well you told the unseen AI model apart from real voices.

Researcher view

Does the skill transfer?

Each dot is one participant. The x-axis is how much training they did; the y-axis is their far-transfer sensitivity (d′) on the strong model they never trained on. The dashed line is chance (d′ = 0). A trained participant who lands well above it was trained only on the weak model, then still discriminated the unseen strong model — that is the transfer signal.

Group A — trained (cue lessons) Group B — exposure-based training – – – chance (d′ = 0)

This view shows real data only. It fetches completed anonymous submissions from the database and computes d′, criterion, and the group comparison live, applying the pre-registered exclusions. Until data collection begins it stays empty — nothing here is simulated.