Open etsea117 opened 1 year ago
Hi @etsea117! I love the idea of advertising recently learned facts. Also, imagine if this is being done in a short podcast like fashion - with 2 voices. I have a feeling that p335 from coqui-ai's vits model might be a great voice. Although, we should decrease her speed - similar to what we are currently doing with p267's voice.
There is a way to extract facts from a document using Textacy. We need to pass an (entity, cue, fragment)
triple for this.
Two years back, I wrote some code to do this, but it is not in a good shape, lol.
Also about adding to-do lists or reminders, I have a question for everyone - Do we want to take this project in a direction which is more like Google Assistant? Or should we keep it close to a radio-like behavior?
Honestly, I am a not sure what the right direction should be.
However, I have received some feedback about fictional ads - and it seems like putting them inside the schema.json
would be a good idea. That way, anyone who does not want to listen to them can turn them off.
Would love to hear your opinions on this.
A suggestion to consider also would be an ability to use scriptures between songs too for a religious themed broadcast. That could be something that people would like to have and take advantage of.
@bornagainpenguin
With the recent commit (535a1836), you can specify the music-genre
to be something like religious
or god
to get a religious themed broadcast.
For instance, something like the following in your ./data/schema.json
:
["music-genre", [["religious", 2], ["god", 1]]],
Tested it locally:
>>> import radio
>>> radio.Recommend().playlist_by_genre("religious")
[('Mahalia Jackson', 'City Called Heaven'), ('Hypatia Lake', 'Joseph and the Divine Intervention of the Recreational Center'), ('Collin Raye', 'When You Say Your Prayers')]
>>> radio.Recommend().playlist_by_genre("religious")
[('Collin Raye', 'When You Say Your Prayers'), ('Sister Rosetta Tharpe', 'The Devil Has Thrown Him Down'), ('Joy Askew', 'Little Darling')]
>>> radio.Recommend().playlist_by_genre("god")
[('The Bronx Casket Co.', 'Savior'), ('Pattern is Movement', 'Elephant'), ('Film School', 'Dear Me')]
Edit: Here is a list of genres this software supports.
@bornagainpenguin I can imagine this and other related DJ-spoken subjects with an extra ["topic", "religion"],
or ["topic", "science"],
that you could (theoretically) add to data/schema.json. Then it would grab sentences from data/gpt/topics.json. 🤔
@ology Aren't these topics currently supported by ./data/genres.csv
?
For instance,
["music-genre", [["religion", 2], ["science", 1]]],
in schema.json
should insert two songs with the tag religion
and one song with the tag science
. I am trying to understand the need for a topic
action here.
Oops. I thought that "music-genre" meant "music only" - not talking. I will experiment before speculating this time!
Oh, wait! My mistake. Are you saying that something like ["topic", "religion"]
would recommend a relevant podcast clip (religious-themed) and not a religious song?
Yes! Spoken word, not music. Podcast would be cool.
I see! Music part is currently supported.
To be honest, recommending podcasts based on genres seems like a research problem.
Here's how we could possibly achieve it:
show_name, show_description, episode_name, episode_description
to predict the genres of that podcast episode.
Probably the dumbest way to do this would be to use GPT-3.5-turbo. If we assume 750 words per execution, this can cost somewhere around $200 for 100k podcasts episodes.
So, we might have to explore something else here.Maybe we should look at some other datasets as well, like 13,000+ Podcasts. It even has genre and podcast description. However, we need to figure out how to get the RSS feed from this.
Let me think about this problem for a while. I'm sure there's an efficient way to do this.
It would be wonderful to be able to customize the fictional ads. I could see this as being linked to a to-do list or reminders lists, allowing someone to advertise important things to themselves. Alternatively, it could be advertising recently learned facts for greater knowledge absorption.