u/Dangerous_Library_40

Happy to fill out yours in return! Drop the link in the comments.

Hey! I built a quick fun survey to see how well people can tell AI-generated music from human-made music. Curious how the community does.

You'll listen to 10 short clips (~45s each), either AI-generated or human-made, and rate each one on a 4-point scale (with a "don't know" option).

Fully anonymous, no sign-in, no personal info beyond a self-rated confidence question at the start.

At the end you get your score, a detective-style profile, and see how you compare to everyone else who's taken it.

Open to anyone, any country, any musical background.

Share your scores! Happy to chat about it in the comments, would love to hear what tipped you off (or fooled you).

Try it out!

Hey! I built a quick fun survey to see how well people can tell AI-generated music from human-made music. Curious how the community does.

You'll listen to 10 short clips (~45s each), either AI-generated or human-made, and rate each one on a 4-point scale (with a "don't know" option).

Fully anonymous, no sign-in, no personal info beyond a self-rated confidence question at the start.

At the end you get your score, a detective-style profile, and see how you compare to everyone else who's taken it.

Open to anyone, any country, any musical background.

Share your scores! Happy to chat about it in the comments, would love to hear what tipped you off (or fooled you).

Try it out!

Genuine question for yall musicians in here.

I've built a small anonymous listening test, 10 short clips, some AI-generated (Suno v5), some human-made (by independent musician without generative AI aid), rated on a 4-point scale. ~5 min, no signup.

What I've found running it so far:

• People who use AI music tools daily average ~67-70% accuracy

• General audience hovers around chance (~43%)

• Self-rated confidence does predict performance (r ≈ 0.38) but moderately: many "confident" listeners still score poorly

My hypothesis is that trained musicians (regardless of AI exposure) might land somewhere in between, sharper ear for production quirks but no specific Suno-pattern recognition.

Would love you to test that!

Try it out! https://parlor.shinyapps.io/audio-short-en/?src=reddit_askmusicians

Genuinely curious what cues you'd use to tell them apart, and whether being a musician helps or hurts.

The selected clips will be used in a follow-up academic research study on how streaming platforms should label AI content, not on training detection models or improving Suno or whatever other model. Skepticism is fair, but the outcome here is consumer protection.

[UPDATE The original link WILL STOP WORKING SOON, if posssible use this one just below :)]
Try it out! https://parlor.shinyapps.io/audio-short-en/?src=reddit_sunoai

Genuinely curious about this specifically.

Built a small anonymous listening test (5 min, no sign-in): 10 short clips, some AI (Suno v 5), some human (from a verified no-ai music library from the 2010s), rated on a 4-point scale.

Where it gets interesting

• Across early general respondents, AI tracks in Pop get caught 60-65% of the time, but AI tracks in Indie Rock fool people almost completely (~25% caught). Suno's Indie Rock is remarkably hard to flag.

• Most listeners over-attribute to AI: they hear human tracks and label them as AI more often than chance. The mere existence of Suno-quality output has shifted what people expect "human" to sound like.

So the question for this sub: does spending time with Suno output make you BETTER at spotting it (trained ear) or WORSE (habituation)? I have a small early signal but not enough data.

[UPDATE]
• Across ~80 respondents, AI Pop gets caught around 60% of the time on average, but AI Indie Rock is WAY MORE uneven , some clips fool almost everyone (only 32% catch it). In this dataset of songs, Suno's Indie Rock can be genuinely indistinguishable.

• The biggest pattern is exposure-driven: AI-music community respondents (r/SunoAI, r/aiMusic) average ~70% accuracy vs ~43% for the general audience. Self-rated confidence now correlates with real performance (r = 0.40), but mostly because experts know they're calibrated. Untrained listeners cluster around chance regardless of how confident they feel.

Not promoting, not monetizing. Just want to see how people who actually use the tool perform.

Hi everyone,

I'm running a pretest to select stimuli for a study on listeners' ability to discriminate AI-generated from human-produced music. Looking for respondents across musical backgrounds.

Task design:

• 10 audio clips (~30s each): some AI-generated, some human-made

• 4-point forced-choice (definitely AI ↔ definitely human)

• Balanced clip sampling, anonymous, ~5 min

Early findings so far:

• Mean accuracy = chance level

• Strong response bias toward "AI" label on human stimuli

• Self-ability ↔ accuracy: r = 0.05 (essentially zero)

• Per-genre asymmetry: AI Pop ≈ 60% detected, AI Indie Rock ≈ 25% detected.

Methodology notes:

• AI: current-gen text-to-music models, prompts matched to the genre/style of each human counterpart

• No personal identifiers collected

Try it out! https://parack.shinyapps.io/audio-short-en/?src=reddit_musiccognition

Happy to discuss in the comments!

Hey! built a quick listening test to see how well people can distinguish AI-generated music from human-made music, and I'd love to get a few responses from people who actually pay attention to this stuff.

How it works:

• 10 short clips, half AI-generated (Suno + Udio), half human-made

• You rate each on a 4-point scale (or pick "don't know")

• Takes ~5 minutes, fully anonymous, no sign-in

• At the end you get a score, a profile, and see how you compare

The interesting bit so far: across 50+ responses, most people score near chance, and there's a strong bias toward labeling things as AI.

Curious to see if this community does noticeably better 😄

Link: https://parack.shinyapps.io/audio-short-en/?src=reddit_aimusic

Happy to chat about methodology or which clips tripped people up!

Happy to fill out yours in return! Drop the link in the comments.

Hey! I built a quick fun survey to see how well people can tell AI-generated music from human-made music. Curious how the community does.

You'll listen to 10 short clips (~45s each), either AI-generated or human-made, and rate each one on a 4-point scale (with a "don't know" option).

Fully anonymous, no sign-in, no personal info beyond a self-rated confidence question at the start.

At the end you get your score, a detective-style profile, and see how you compare to everyone else who's taken it.

Open to anyone, any country, any musical background.

Share your scores! Happy to chat about it in the comments, would love to hear what tipped you off (or fooled you).

Try it out!

Hey! I built a quick fun survey to see how well people can tell AI-generated music from human-made music. Curious how the community does.

You'll listen to 10 short clips (~45s each), either AI-generated or human-made, and rate each one on a 4-point scale (with a "don't know" option).

Fully anonymous, no sign-in, no personal info beyond a self-rated confidence question at the start.

At the end you get your score, a detective-style profile, and see how you compare to everyone else who's taken it.

Open to anyone, any country, any musical background.

Share your scores! Happy to chat about it in the comments, would love to hear what tipped you off (or fooled you).

Try it out!