/soundchat

Snapchat for Sound 🔑

Primary LanguagePythonMIT LicenseMIT

Khaled

soundchat

audiogrep forked from https://github.com/antiboredom/audiogrep.

Setting up audiogrep

Requirements

Install using pip

pip install audiogrep

Install ffmpeg with Ogg/Vorbis support. If you're on a mac with homebrew you can install ffmpeg with:

brew install ffmpeg --with-libvpx --with-libvorbis

Finally, install CMU Pocketsphinx. For mac users I followed these instructions to get it working:

brew tap watsonbox/cmu-sphinx
brew install --HEAD watsonbox/cmu-sphinx/cmu-sphinxbase
brew install --HEAD watsonbox/cmu-sphinx/cmu-sphinxtrain # optional
brew install --HEAD watsonbox/cmu-sphinx/cmu-pocketsphinx

Setting up khaled

~ How do I use it?

  1. edit the configuration in the flaskr.py file or export an KHALED_SETTINGS environment variable pointing to a configuration file.

  2. install the app from the root of the project directory

    pip install --editable .

  3. Instruct flask to use the right application

    export FLASK_APP=khaled

  4. brew install postgresql

  5. Install Cockroach DB, and run a multi-node cluster. Don't run the sample SQL commands.

  6. Setup the database: bash setup-database.sh (Make sure cockroach is in the path)

  7. now you can run khaled:

    flask run

    the application will greet you on http://localhost:5000/

~ Is it tested?

You betcha. Run python setup.py test to see the tests pass.

Audiogrep

Audiogrep transcribes audio files and then creates "audio supercuts" based on search phrases. It uses CMU Pocketsphinx for speech-to-text and pydub to stitch things together.

Here's some sample output.

##How to use it First, transcribe the audio (you'll only need to do this once per audio track, but it can take some time)

# transcribes all mp3s in the selected folder
audiogrep --input path/to/*.mp3 --transcribe

Then, basic use:

# returns all phrases with the word 'word' in them
audiogrep --input path/to/*.mp3 --search 'word'

The previous example will extract phrase chunks containing the search term, but you can also just get individual words:

audiogrep --input path/to/*.mp3 --search 'word' --output-mode word

If you add the '--regex' flag you can use regular expressions. For example:

# creates a supercut of every instance of the words "spectre", "haunting" and "europe"
audiogrep --input path/to/*.mp3 --search 'spectre|haunting|europe' --output-mode word

You can also construct 'frankenstein' sentences (mileage may vary):

# stupid joke
audiogrep --input path/to/*.mp3 --search 'my voice is my passport' --output-mode franken

Or you can just extract individual words into files.

# extracts each individual word into its own file in a directory called 'extracted_words'
audiogrep --input path/to/*.mp3 --extract

Exporting to: extracted_words/i.mp3
Exporting to: extracted_words/am.mp3
Exporting to: extracted_words/the.mp3
Exporting to: extracted_words/key.mp3
Exporting to: extracted_words/master.mp3

###Options

audiogrep can take a number of options:

####--input / -i mp3 file or pattern for input

####--output / -o Name of the file to generate. By default this is "supercut.mp3"

####--search / -s Search term

####--output-mode / -m Splice together phrases, single words, fragments with wildcards, or "frankenstein" sentences. Options are:

  • sentence: (this is the default)
  • word
  • fragment
  • franken

####--padding / -p Time in milliseconds to add between audio segments. Default is 0.

####--crossfade / -c Time in milliseconds to crossfade audio segments. Default is 0.

####--extract / -x

####--demo / -d Show the results of the search without outputing a file