Lyrics To Song AI - AI Music Generator

Audio Spectrogram Viewer Tool

FFT:
Color:
dB: -90~-10

Drop or click to upload

Visualize frequencies in any audio file

or try a demo
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  • ✅ Upload an audio file to analyze audio frequency content
  • ✅ The spectrogram shows frequency (vertical) over time (horizontal)
  • ✅ Brighter colors indicate stronger frequencies at that moment
  • ✅ Adjust FFT size for frequency resolution (higher = more detail, slower)
  • ✅ Choose a color scheme that works best for your analysis
  • ✅ Adjust dB range to focus on different intensity levels

Audio Source

Upload audio files in MP3, WAV, FLAC, OGG, M4A formats for frequency analysis and visualization. The audio spectrogram viewer supports all common audio formats for real-time audio analysis.

Spectrogram

Real-time frequency visualization showing audio spectrum over time. The spectrogram displays frequency (vertical axis) over time (horizontal axis) with color intensity indicating amplitude. This frequency analyzer provides detailed sound spectrum analysis.

Visualization Settings

Configure FFT size from 512 to 8192 bins for frequency resolution control. Adjust Min dB and Max dB range to focus on different intensity levels. Select color schemes including Viridis, Hot, Cool, and Grayscale for optimal audio visualization. Higher FFT size provides more frequency detail but slower processing for this FFT analysis tool.

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Audio AnalysisNo Installation

Free Spectrogram Viewer - Visualize Audio Frequencies

Visualize audio frequency content over time with customizable FFT, color schemes, and demo samples. Perfect for engineers, researchers, and sound designers.

Browser-based spectrogram with advanced FFT analysis and privacy-friendly processing.
Start Analyzing AudioView Tutorial
512 – 8192
FFT sizes
File Upload + 3 Demos
Inputs
4 scientific palettes
Color schemes
Free
Price

Why creators choose our AI Song Generator

Value propositions

Professional-Grade Analysis

Studio-quality spectrogram analysis with customizable FFT sizes from 512 to 8192 bins. Get detailed frequency resolution comparable to expensive audio analysis software.

Real-Time Processing

Analyze audio files or live microphone input with instant visualization. Perfect for live sound analysis, instrument tuning, and acoustic measurements.

Flexible Visualization

Choose from multiple scientifically-designed color schemes including Viridis, Hot, Cool, and Grayscale. Customize dynamic range for optimal visibility.

Universal Compatibility

Works entirely in your browser with no installation required. Supports all major audio formats including MP3, WAV, FLAC, OGG, and M4A.

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Workflow overview

Follow these steps to move from idea to final mix

  1. 1
    Upload an audio file or click 'Record from Mic' to analyze live microphone input.
  2. 2
    Choose FFT size (higher = more frequency detail), color scheme, and dB range.
  3. 3
    Click play (for files) or watch real-time (for mic). The spectrogram builds from left to right.
  4. 4
    Vertical axis = frequency, horizontal = time. Brighter colors = stronger frequencies.

What you can create with AI Song Generator

Inspiration for different creator workflows

Audio Analysis

Identify frequency content and harmonics

Sound Design

Visualize synth patches and effects

Music Research

Study instrument timbre and overtones

Voice Analysis

Analyze speech formants and pitch

Frequently asked questions

Answers for licensing, quality, and workflow

What is a spectrogram?+
A spectrogram is a visual representation of the frequency spectrum of a signal over time. The vertical axis shows frequency, the horizontal axis shows time, and color/brightness indicates the amplitude (strength) of each frequency at each moment. It's an essential tool for audio analysis, allowing you to see both the frequency content and how it changes over time in a single visualization.
What should I set FFT size to?+
Higher FFT sizes (4096, 8192) give better frequency resolution but lower time resolution. Lower sizes (512, 1024) give better time resolution but blur frequencies. For speech, try 2048. For music analysis, try 4096. For percussive sounds, use lower values like 1024 to capture quick transients.
What do the colors mean?+
Colors represent amplitude (volume) at each frequency. In most schemes, darker colors = quiet/absent, brighter colors = loud/present. The exact mapping depends on your chosen color scheme and dB range settings. The Viridis color scheme uses a perceptually uniform scale from purple (quiet) to yellow (loud).
Why adjust the dB range?+
The min/max dB settings control which amplitude levels are visible. Lower the min dB to see quieter sounds, raise the max dB to reduce saturation from loud sounds. Adjust until you see useful detail. A typical starting range is -90 dB to -10 dB, but this varies based on your audio source.
Can I save the spectrogram image?+
Currently, the tool focuses on real-time analysis. You can take a screenshot of the browser window to capture the spectrogram visualization. Use your operating system's screenshot tool (Windows: Windows+Shift+S, Mac: Command+Shift+4) for best results.
What audio formats are supported?+
The viewer supports all common audio formats that your browser can decode: MP3, WAV, OGG, M4A, FLAC, and more. For best analysis quality, use lossless formats like WAV or FLAC. Compressed formats like MP3 may show artifacts in the high-frequency range.
How does FFT analysis work?+
FFT (Fast Fourier Transform) converts audio from the time domain to the frequency domain. It analyzes small windows of audio and determines which frequencies are present at each moment. The FFT size determines how many frequency bins are analyzed - larger sizes provide more frequency detail but less time precision.
Can I analyze microphone input in real-time?+
Yes! Click the 'Record from Mic' button and grant microphone permissions. The spectrogram will display real-time frequency analysis of your microphone input. This is perfect for analyzing live instruments, voice, or environmental sounds.
What's the difference between color schemes?+
Viridis provides perceptually uniform colors ideal for scientific analysis. Hot uses red-yellow tones for high contrast. Cool uses blue-green tones for a calmer appearance. Grayscale is best for printing or color-blind accessibility. Choose based on your preference and analysis needs.
How do I identify specific frequencies?+
The vertical axis shows frequency in Hz. Common reference points: 440 Hz is concert A, human voice fundamentals are typically 80-250 Hz, consonants appear above 2 kHz, and musical overtones form horizontal bands at integer multiples of the fundamental frequency.
Why do I see horizontal bands in music?+
Horizontal bands represent harmonic content - the fundamental frequency and its overtones. Musical instruments produce harmonics at integer multiples of the fundamental (2x, 3x, 4x, etc.). The pattern and strength of these harmonics determine the timbre or tone color of the sound.
Can I use this for speech analysis?+
Absolutely! Spectrograms are widely used in speech research. You can identify formants (resonant frequencies of the vocal tract), observe pitch patterns, distinguish between vowels and consonants, and analyze speech characteristics. Use FFT sizes around 2048 for balanced speech analysis.
Is my audio data uploaded to a server?+
No! All processing happens entirely in your browser using the Web Audio API. Your audio files never leave your device, ensuring complete privacy. This also means the tool works offline once the page is loaded.
What causes noise in the spectrogram?+
Random noise appears as granular texture across all frequencies. Electrical noise (hum) shows as horizontal lines at 50 Hz or 60 Hz and harmonics. Recording artifacts may appear as vertical lines. Lower the min dB threshold to make background noise more visible.
How can I compare two audio files?+
Analyze each file separately and take screenshots for comparison. Look for differences in frequency distribution, harmonic content, and noise floor. This is useful for comparing audio quality, identifying mastering differences, or verifying audio processing effects.

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