songsee

To generate an audio spectrogram, run the songsee CLI with your track file to produce a PNG image visualizing frequency content over time. You can visualize specific features by passing the --viz flag with options like mel, chroma, hpss, loudness, and mfcc.

You can visualize multiple audio feature panels including mel, chroma, hpss, selfsim, loudness, tempogram, mfcc, and flux. These feature panels provide detailed visualizations of spectral content for music research, media QA, and analysis presentations.

FFmpeg may be relied upon to decode various audio formats for spectrogram generation. You need compatible audio files and the songsee binary, while piping standard input requires specifying the format explicitly to correctly process the incoming audio data.

You can visualize a specific time slice of an audio track by using the --start and --duration flags. Specifying a start time and duration extracts that segment, outputting the visualization to a designated file like slice.jpg.

The best way to output spectrograms as PNG images is using the CLI with the --format png flag. You can direct the output to a specific file using the -o option, which is useful for integrating visualizations into automated audio analysis workflows.

Yes, songsee supports piping audio via standard input by using a hyphen as the input argument. You must specify the output format, such as --format png, to ensure the piped audio data is correctly processed and saved.