SiliconSense
Unlock all · $26.87
← Lab

🎧 Audio → Prompt — demo

Drop a reference mp3 (up to 10 MB) — AI listens and returns: era, BPM, instruments, production, vocal, Suno prompt, vocal anchor, and 3 closest catalog artists. Pro-model Gemini 3.1, ~30–60 sec.

User input
File: sample-track.mp3 (3:24)
Hint: (none)
Hint is optional. AI listens to the full track and detects era, instruments, vocal, lyrical themes.
Quick summary
Era: 2010s · Genre: pop-punk
BPM: 165 · Language: Russian
🎨 Suno style prompt
2010s pop-punk and emo rock, youthful male vocals with a bright nasal timbre and gritty shouted energetic delivery, overdriven electric guitars with thick distortion, heavy down-picked bass guitar, punchy acoustic drum kit augmented with a triggered snare, modern rock compression with wide stereo guitar panning, vocal doubling and slight saturation, 160-170 BPM, angsty, highly energetic, desperate and driving mood, intro-verse-chorus-verse-chorus-bridge-outro structure, Russian language lyrics focusing on heartbreak, burning bridges, and emotional desperation.
🎙️ Vocal Anchor
[Vocal: male, youthful, bright, nasal timbre, sung and shouted delivery, gritty texture, mid-high pitch, angsty phrasing, doubled, saturated]
Instruments
overdriven electric guitars heavy down-picked bass punchy drum kit triggered snare subtle synth pads
Production
modern rock compression wide stereo panning vocal doubling drum sample layering
Mood
angsty energetic desperate driving
Subgenres
emo rock alternative rock post-hardcore
Closest catalog artists
Green Day · EN · 1990s · pop-punk
Avril Lavigne · EN · 2000s · pop-punk
Olivia Rodrigo · EN · 2020s · pop-punk
Analysis
Этот трек звучит как типичный поп-панк и эмо-рок 2010-х годов с плотным, современным продакшеном. Широкие стерео-гитары с перегрузом и мощная ритм-секция с триггерными барабанами создают агрессивную, драйвовую стену звука. Вокал сочетает чистый, слегка назальный тембр с эмоциональными срывами на крик, что идеально подчёркивает подростковую тоску и отчаяние в лирике.
99 𝄞 per analysis. Pro-model listens to actual audio — much more accurate than tag-only generators. Notes auto-refund on AI failure.
Upload your track →