The easiest way to install wav2vec is to use pip to install from the Python Package Index:

Depending on your system, in order to install in the Python 3 path, you may have to use pip3 instead of pip.

Alternatively, clone the git repository:

Now you can run wav2vec.py directly:

Or install the package with PIP:

usage: wav2vec [-h] [--format {PostScript,SVG,CSV}] [--width WIDTH]
               [--height HEIGHT] [--stream BS] [--downtoss N]
               [--log {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
               filename

Convert WAV and AIFF files to vector (SVG, PostScript, CVS) graphics.

positional arguments:
  filename              The WAV file to read

optional arguments:
  -h, --help            show this help message and exit
  --format {PostScript,SVG,CSV}, -f {PostScript,SVG,CSV}
                        The output format, one of: SVG, CSV, PostScript.
                        Default is SVG.
  --width WIDTH         Maximum width of generated SVG (graphic will be scaled
                        down to this size in px)
  --height HEIGHT       Maximum height of generated SVG (graphic will be
                        scaled down to this size in px). Note that this scales
                        according to the highest possible amplitude (given the
                        sample bit depth), not the highest amplitude that
                        actually occurs in the data.
  --stream BS           Stream the input file size in chunks (of BS number of
                        frames at a time) and process/format each chunk
                        separately. Useful for conserving memory when
                        processing large files, but note that multi-channel
                        paths will be split up into BS-sized chunks. By
                        default BS=0, which causes the entire file to be read
                        into memory before processing.
  --downtoss N          Downsize by keeping only 1 out of every N samples.
  --log {DEBUG,INFO,WARNING,ERROR,CRITICAL}
                        Set the logging level.

The output is sent to stdout.

Output format

$ wav2vec filename.wav --format PostScript > output.ps

Scale output

$ wav2vec filename.wav --width 500 --height 350 > output.svg

Stream input file

$ wav2vec filename.aiff --stream 1024 > output.svg

Downsampling

You can also import wav2vec in order to convert wave files to the supported output formats in your own Python scripts. The package provides two main classes: WavDecoder and the abstract Formatter (and the concrete implementations: SVGFormatter, PSFormatter, and CSVFormatter). The documentation is currently contained in the source files; look at main.py for an example of usage.

The WavDecoder class wraps the standard library’s wave and aifc modules and provides an easy way to read and decode WAV/AIFF files. Use it as a context manager to ensure close() is called. Use it as an iterator to process all frames:

See wav2vec/WavDecoder.py.

The Formatter class is an abstract base class which defines the interface for all formatters which output WAV data in textual formats. Each concrete subclass of Formatter takes a WavDecoder object in its constructor which is what is responsible for reading/decoding data from a WAV or AIFF file.

The output() method will stream output to a file (stdout by default), but the entire output string can be captured using the str() method.

See the formatter package.

SVG

$ wav2vec tests/valfiles/snd/test-16-stereo.wav > test.svg
$ inkscape test.svg

PostScript

$ wav2vec tests/valfiles/snd/test-16-stereo.wav -f PostScript > test.ps
$ ps2pdf test.ps
$ evince test.pdf

CSV

$ wav2vec tests/valfiles/snd/test-16-stereo.wav -f CSV --height 0 > test.csv
$ libreoffice test.csv

To run unit and validation tests (requires python3):

Creating a custom formatter is simply a matter of subclassing Formatter and overriding the five abstract methods it defines. Use the included SVGFormatter, PSFormatter, or CSVFormatter as a template (see wav2vec/formatter/formatters.py).