PaperWhisperer is a Python application that keeps you up-to-date with research papers. How? It retrieves the latest articles from arXiv on a topic, by performing a keyword-based search. Then, it creates vocal summaries of the articles using Text-To-Speech and stores them to disk.


To install the package, move to the root of the repo and type in the console:

$ pip install .

If you plan to develop the package further, install the package in editable mode also installing the packages necessary to run unittests:

$ pip install -e .[test]


To run unittests, issue the following command from the root of the repo:

$ pytest

Package structure

The package is divided into 2 sub-packages:

  • retrieval
  • tts

retrieval contains data structures and facilities necessary to retrieve articles from arXiv. Under the hood, the app uses arxiv, a Python package that is a wrapper around the arXiv free API.

tts has facilities to generate speech renditions of text-based article summaries. The summary of an article consists of its title, authors, and abstract. Speech synthesis is performed using Google Cloud Text-To-Speech.

Setting up Google Cloud Text-To-Speech

PaperWhisperer uses Google Cloud Text-To-Speech to synthesise speech.

In order to be able to use this service, you should:

  1. create an account on Google Cloud,
  2. create a Cloud Platform project,
  3. enable the Text-To-Speech API in the project
  4. setup authentication
  5. download a Json private key

More info on how to set up Google Cloud Text-To-Speech

Environment variables

The app uses an environment variable called GOOGLE_APPLICATION_CREDENTIALS to connect to Google Cloud Text-To-Speech safely.

In config.yml, set GOOGLE_APPLICATION_CREDENTIALS to the path of the Json private key you previously downloaded while setting up the Google service.

Without this step, you won't be able to connect to Google Cloud Text-To-Speech, and the app will throw an error.

How to create summaries

To create summaries for a keyword search, use the create_summaries entry point. This is the only console script of the package and the main entry point of the application.

Below is an example of how you can run the script:

$ create_summaries "generate chord progressions" 100 /save/dir 40

The script takes 4 positional arguments:

  • keywords used for searching articles (more than one keyword is possible)
  • maximum number of articles to retrieve
  • directory where to store vocal summaries
  • retrieve articles no older than this integer value in days


PaperWhisperer depends on the following packages:

  • arxiv==1.2.0
  • google-cloud-texttospeech
  • python-dotenv

YouTube video

Learn more about PaperWhisperer in this project presentation video on The Sound of AI YouTube channel.