Phoenix10.1

Phoenix10.1 is a software to generate personalized pre-recorded internet radios that has a text-to-speech based radio jockey.

Here's a demo to understand what it sounds like!

What can it do?

This radio jockey is capable of playing your favorite songs, including tracks from your preferred artist, genre, or Billboard chart. It can automatically discover and play fascinating clips from your preferred podcasts, provide weather updates, and deliver daily news.

For a more authentic radio experience, it brightens up your day with fictional company ads, conducts daily QnA with the audience, and shares interesting "On this day..." facts.

Installation

It is recommended to use Python 3.10 or newer to run the code.

Quick Start

If you're using a Debian-based distribution, you can install all dependencies using install.sh:

sh install.sh

Manual

This software requires ffmpeg and espeak. To install them on MacOS:

brew install ffmpeg espeak

To install them on Linux (Debain-based):

sudo apt-get install ffmpeg espeak

For Windows users, to setup and use ffmpeg, follow this guide from Stack Exchange. Moreover, to setup espeak, use this tutorial from Stack Overflow.

To install the Python dependencies, use:

pip3 install -r ./requirements.txt

The software also requires installing punkt from nltk. In a Python shell, use the following code to install punkt:

import nltk
nltk.download("punkt")

To generate TTS (text-to-speech), Coqui-ai's vits model is used. We recommend running a generic TTS command on your shell as this will prompt TTS to automatically install the vits model.

tts --text "I am excited to demo Phoenix ten point one" --model_name tts_models/en/vctk/vits --speaker_idx p267 --out_path temp.wav

The vits model requires around 150 MB of storage.

Creating your radio broadcast

To create your own radio, start by updating the default schema in ./data/schema.json.

Each action in schema.json is a list with two indices, one mentions the action and another mentions the characteristic of that action. Actions available are:

• up
  • routine to start the radio broadcast
  • characteristic value is ignored
• music
  • fetches and streams music
  • characteristic should contain list of song names
• local-music
  • streams music using locally stored songs
  • characteristic should contain either:
    • list of paths to the audio files
    • list of lists of the format [album_path, num_of_songs]
• music-artist
  • fetches and streams music (based on the artist names)
  • characteristic should contain list of lists of the format [artist_name, num_of_songs]
• music-genre
  • fetches and streams music (based on some specific genres)
  • characteristic should contain list of lists of the format [genre, num_of_songs]
  • Here is a list of genres supported by Phoenix10.1.
• music-billboard
  • fetches and streams music from Billboard charts
  • characteristic should contain list of lists of the format [chart_name, num_of_songs]
• podcast
  • fetches an interesting clip from a podcast
  • characteristic should be a list of the format [podcast_rss_link, max_clip_duration_in_mins]
• weather
  • broadcasts the weather
  • characteristic should contain city name. Use null to fetch weather using your IP address.
• news
  • broadcasts the news using rss feeds. The rss feeds can be updated in ./data/rss.json.
  • characteristic should be a list of the format [category, num_of_news_items]
• fun
  • broadcasts a On this day... fact
  • characteristic is ignored
• end
  • routine to end the broadcast
  • characteristic is ignored
• no-ads
  • removes fictional advertisements from the broadcast. This action should come before up
  • characteristic value is ignored
• no-qna
  • removes the daily QnA from the broadcast. This action should come before up
  • characteristic value is ignored

Run

Once schema.json is configured, run the software using:

python3 radio.py

Your entire broadcast would be stored in a radio.mp3 file.

TTS configuration

You can modify the voice of the radio jockey, the name of your radio station/host, and the volume of the background music by editing the ./config.json file. To experiment with different voices, you can use Coqui-ai's vits model with the following command:

tts-server --model_name tts_models/en/vctk/vits

For advice on selecting the best voices, check out this discussion.

The volume of the background music can be adjusted between 0.1 and 2. A value of 0.1 will turn off the background music, while a value of 2 doubles its volume.

Contributing

We always welcome and greatly appreciate contributions! You can contribute in various ways, like by reporting and fixing bugs or suggesting and implementing new features. To start contributing, you can either submit a pull request or open an issue.

If you're submitting a pull request, please make sure to run pylint before submitting. Although it's not mandatory, performing unit tests on your code is highly encouraged.

To run the unit tests, use this command (from the root directory):

python3 -m coverage run --omit */site-packages/* -m unittest

We also recommend using mutation testing with mutmut. To execute mutmut, run this command (once again from the root directory):

mutmut run --paths-to-mutate ./radio.py --tests-dir ./tests/ --runner 'python3 -m unittest'

Bear in mind that mutation testing is a costly means of evaluating your test suite and can take several hours. So, only use this while suggesting a major change.

License

The code is open-sourced under the MIT License.

Acknowledgements

Every software stands on the shoulders of giants, and this is no different!

• The authors would like to thank Coqui-ai and their work on TTS (licensed under Mozilla Public License 2.0).
• The logic to generate random identities is from rig and the names database (fnames.txt, lnames.txt, locdata.txt) is from the US Census database.
• The dataset in ./data/genres.csv is curated from the The Million Song Dataset.
  • The Million Song Dataset was created under a grant from the National Science Foundation, project IIS-0713334. The original data was contributed by The Echo Nest, as part of an NSF-sponsored GOALI collaboration. Subsequent donations from SecondHandSongs.com, musiXmatch.com, and last.fm, as well as further donations from The Echo Nest, are gratefully acknowledged.
• The background music is Woke up this Morning Theme by Lobo Loco and is licensed under a Attribution-ShareAlike 4.0 International License.
• The questions are from icebreakers which is licensed under MIT License. Some of the responses were manually curated from character.ai. From their TOS:
  • As to a user interacting with a Character created by another user or by Character AI, the user who elicits the Generations from a Character owns all rights in those Generations and grants to Character AI a nonexclusive, worldwide, royalty-free, fully paid up, transferable, sublicensable, perpetual, irrevocable license to copy, display, upload, perform, distribute, store, modify and otherwise use any Generations.
• The fictional advertisement and intros/outros were curated using the gpt-3.5-turbo model. We followed the Sharing & Publication Policy of OpenAI and acknowledge that we have reviewed, edited, and revised the language of the content to our preference. We take ultimate responsibility for the content generated.
• The Logo was generated using Open AI's Dall-E 2.