Generate a Mel Spectrogram PNG
Upload audio and render the mel-frequency view used by speech, music, and audio-ML pipelines. Tune FFT, hop, mel bands, scale, palette, and output size locally.
About this tool
Mel spectrograms compress an audio clip into the time-frequency view used by many speech, music, keyword-spotting, and audio-classification pipelines. This tool decodes the audio locally, applies an STFT, maps FFT bins through triangular mel filters, scales the energy, and renders the result as a PNG image.
Worked example: upload a WAV voice clip, choose the “Speech 16 kHz compact” preset, and download the PNG. The output uses 80 mel bands, a 1024-sample FFT, a 256-sample hop, an 8 kHz high-frequency edge, and a 16 kHz analysis sample rate — a compact diagnostic view for speech models.
Limits: input audio is capped at 24 MiB and 4,000,000 decoded samples. Very short clips may need center=true or a smaller FFT. width=0 and height=0 use the natural matrix size: one pixel per frame and one row per mel band.
FAQ
Is this the same as an MFCC extractor?
No. A mel spectrogram keeps the mel-band energy image before the DCT step. MFCC tools convert the log-mel bands into cepstral coefficients for tabular features; this tool renders the mel bands directly as a PNG for inspection or image-based pipelines.
Which settings match common audio-ML examples?
A common starting point is n_fft=2048, hop_length=512, n_mels=128, mel_scale=slaney, scale=db, and center=true, which mirrors the defaults many librosa-style examples use. Speech pipelines often resample to 16 kHz and use 64 or 80 mel bands.
Why are low frequencies at the bottom of the PNG?
That orientation matches the way spectrograms are usually read: time runs left to right and frequency rises from bottom to top. The summary reports the loudest mel-band frequency so you can sanity-check tones and hums.
What do `peak` and `full_scale` dB references change?
peak maps the loudest cell in the clip to the brightest color, which is useful for visual contrast. full_scale keeps the reference tied to digital full scale, so quiet files stay visibly dimmer and are easier to compare across clips.
Developer & Automation Access
Run it from the terminal
Same engine as this page, headless — via the gizza CLI:
gizza tool mel-spectrogram-generator 'url=https://example.com/input' 'input_format=base64' 'n_fft=2048' 'hop_length=0' 'n_mels=128' 'fmin=0' 'fmax=0' 'mel_scale=slaney' 'window=hann' 'scale=db' 'top_db=80' 'db_reference=peak' 'colormap=magma' 'width=1000' 'height=400' 'channel=mix' 'center=true' 'resample_hz=0'New to the CLI? Get gizza →
Open it by URL
Pre-fill and auto-run this tool with query parameters — the names match the API/CLI:
https://gizza.ai/tools/mel-spectrogram-generator/?url=https://example.com/input&input_format=base64&n_fft=2048&hop_length=0&n_mels=128&fmin=0&fmax=0&mel_scale=slaney&window=hann&scale=db&top_db=80&db_reference=peak&colormap=magma&width=1000&height=400&channel=mix¢er=true&resample_hz=0Machine-readable descriptor: tool.json — title + parameters JSON Schema for agents.