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License: MIT License
Creates personalized radio stations with your own radio jockey!
License: MIT License
Many playtesters have asked for this feature. It is true that the current voice is quite a nice human voice, however, choices are personal. Having this feature seems quite useful - integrate different voices from coqui-ai's vits model.
Helpful: coqui-ai/TTS#1891
When we use the podcast action, at times we might get an error like this:
Traceback (most recent call last):
File "radio.py", line 967, in <module>
dialogue.flow()
File "radio.py", line 739, in flow
speech = self.podcast_dialogue(rss_feed)
File "radio.py", line 489, in podcast_dialogue
"You know, I love listening to podcasts. "
KeyError: 'itunes_author'
This happens because no 'itunes_author' metadata was provided by the RSS feed. We need a fallback condition here.
One of the playtesters had the following to say when the following:
I am curious, was the voice in the demo too hard to hear? Can you point out some specific issues with it, so that we can fix it.
It was a combination of my personal hearing issues, the lack of inflection on the bot's voice (though with that accent it kind of worked for it a bit because it seemed so cool and laid back in the demo,) and possibly the background music being a slight bit too loud for the voice and they sort of blended together a bit for me. After a while I simply could not focus on it.
Adjusting volume seems quite useful.
The logging system we currently have is quite difficult to read and debug. To address this issue, our first step would be to eliminate the unnecessary noise generated by Coqui-ai's TTS and FFmpeg.
However, it may be challenging to suppress TTS logs as they currently rely on print statements rather than the logging
module. To solve this problem, we could use a method similar to the one outlined here: https://stackoverflow.com/a/45669280/7543474 - to remove any excess print statements.
While we don't want to overwhelm the user with too many logs, we still want them to have a clear understanding of the overall flow. Ideally, they should be aware of what is being generated and in what order.
Sometimes, there can be a disparity between the song title/artist introduced by the radio host and the actual song that plays afterwards. This is due to the fact that song fetch and metadata fetch have separate methods. As a result, the search rankings outputted during the fetch actions differ, leading to the mismatch.
The song fetch logic (in the music
method) relies on the song name and, potentially, an artist name. However, the metadata fetch depends solely on the song name.
To address this issue, we could potentially utilize the --add-metadata
tag in youtube-dl
. If this method fails to bring in the necessary metadata, we would then resort to the older method. I believe that this approach would significantly improve the matching accuracy.
It would also be nice to check if yt-mdl
can automatically handle this for us within the music
method.
In addition to the ability to set songs by searching song title and artist and song title together, it might offer some simplicity to the enduser to be able to specify genre and a number of songs, which would offer a bit of randomness to the process and make listening more of a surprise. There would need to be a way to record for lookup which songs were played previously in a log of some sort to avoid being bombarded with the same songs over and over again but it could add some variety, especially if it were possible to specify a song, then several songs in a genre before returning to a specific song or two.
Donno how to chat with you, Parth. I just wanted to say that your improvements are fantastic. The tracks in my personal collection are named properly now, by the DJ. Woo!
-Gene
Users should have fine-grained control over daily QnA part, just like they do for fictional ads with no-ads
action.
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.
At the moment, only song names are supported in schema. A nice iteration would be to add support for artist names - kind of like Pandora.
Just wondering if this would add some benefits over the current Coqui-ai's vits model?
The beta can be found here.
There may be times when users have their songs stored locally. In these cases, they may not need to use youtube-dl
to retrieve the songs again. It would be a good idea to add support for locally stored songs.
Ideally, this feature should allow for both the specific path name of the song and a directory name for retrieving a set of random songs. Perhaps an intelligent fetch could automatically detect artist names as well?
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