Audio Spectrum Analysis
What Can the Spectrum Analyzer Do?
The Spectrum Analyzer is a free online tool that uses the Web Audio API to analyze audio signals in real-time, decomposing sound into different frequency components and displaying them as a visual spectrum. It supports both real-time microphone input and local audio file upload, helping users intuitively understand audio frequency characteristics.
Core Features
- Real-time Spectrum Analysis: Uses FFT algorithm to decompose audio signals in real-time, visualizing amplitude of each frequency component
- Multiple Input Sources: Supports real-time microphone recording and local audio file upload (MP3/WAV/OGG/FLAC)
- Multiple Display Modes: Bar chart, line chart, and mirror display for different visualization styles
- Adjustable Parameters: Customizable FFT size and smoothing coefficient for different analysis needs
- Peak Detection: Real-time display of peak frequency, average amplitude, and sample rate
How to Use
1. Click the "Microphone" button to authorize microphone access, or click "Upload Audio" to select a local audio file
2. Adjust FFT size and smoothing parameters to optimize analysis results
3. Select display mode (Bars/Line/Mirror) to view different spectrum styles
4. Observe peak frequency and amplitude information to analyze audio characteristics
Use Cases
Case 1: Audio Production & Mixing
Music producers use spectrum analysis to check frequency balance in mixes, identifying frequency conflicts and resonance issues.
Case 2: Acoustic Environment Analysis
Use the microphone to analyze room acoustic characteristics in real-time, identifying standing waves and resonant frequencies.
Case 3: Equipment Fault Diagnosis
Analyze the spectral characteristics of equipment running sounds to identify abnormal frequency components for fault diagnosis.
Technical Background
The Fast Fourier Transform (FFT) is the core algorithm for spectrum analysis, converting time-domain signals to frequency-domain representations. FFT size determines frequency resolution (Δf = sample rate / FFT size). Larger values provide higher frequency resolution but lower time resolution. The smoothing coefficient controls spectrum display smoothness. The human audible range is 20Hz-20kHz, with different frequency bands corresponding to different sound characteristics.