Exploring Aspects Of AI Music Generation

Cartoon Music Machine by AI

Image collage created by AI via Bored Humans website

This post is really just an attempt of mine to gather together some of the explorations I have been doing to see what progress is being made with AI technology and the making of music and sound. It’s all pretty strange worlds out there right now.

Some sites are starting to use inputted text from users to generate sound and music. Others are built where the user does not have agency to create music, only to experience songs based on some choices, like mood or genre or artist. None of it, to my ears, sounds authentically human (yet?).

Here are a few sites I’ve explored:

Riffusion takes a phrase of writing put into its engine and moves it into a sort of song pattern, and the site features a rolling musical pattern that is designed to make visual the algorithmic patterns being used. Here is one that I did for a Daily Create that featured Riffusion with the phrase: A haiku is a moment in time. See the details on how Riffusion works — it is pretty fascinating. (Free to use)

Google is developing its own text-to-music AI generator, called MusicLM, which takes inputted text and creates a moody, evocative soundtrack to go with the words. There are plenty of intriguing examples, although it seems like Google is maybe working to figure out the copyright logistics of its database, where it has collected sound and loops that its machine uses to generate the soundtracks from text. Google also has the Magenta Project, another AI development that’s been around for bit, and the Magenta site does feature some examples of how it is being used to merge creativity with machine learning. (MusicLM not yet publicly available for use other than samples – Magenta data can be used for projects, I think)

OpenAI — the group behind ChatGPT — has Jukebox on its drawing board, and the algorithms are being fed music and sound and song lyrics, and it is learning how to create music tracks in the styles of those artists. It’s a bit jarring, to me, to hear how the machine uses Ella Fitzgerald as its source. OpenAI also has something called MuseNet, which seems similar to Jukebox. (Not yet publicly available other than samples)

The Bored Humans website has an AI Music Generator that uses neural network learning to produce entirely computer-generated songs, with lyrics. None of it is much fun to listen to for any extended period of time, in my opinion, but that it is being done is something to take note of, and worth playing around with. They even host a Lyric Generator.  (Free to use)

Soundraw is a site that generates music by mood, and gives you a handful of song options to choose from. I found many of the tracks sounded the same, but I didn’t do a full explore of the possibilities there. Here is a track for the mood of “hopeful” as an example. (Free to use, but requires account for any download)

Melobytes is another odd one, but it gives you plenty of options to manipulate the sounds the AI generates as a sort of “song” from text — although every time I have used Melobytes, the song sounds pretty jarring and off-kilter to me. (Account required).

And I am sure there are others out there, too, and more to come, no doubt.

Whether this is all good for the field of music creation or not will be debated for a long time, I am sure. Just as ChatGPT and its field of chatbots has many thinking deeply on the art and creative act of writing, so too will the field of AI music generators have musicians wondering about how the field of sound is being transformed by algorithms, and what it means to be an artist in the field of music. (I also worry these AIs will put a lot of musicians who work on films and television and other media venues out of work, just as the DJ put many live bands out of work for weddings and other gigs.)

Peace (and sound),


Is Making Music With The Machine The Same As Writing With The Machine?

Music Machine
Music Machine flickr photo by Dogtrax shared under a Creative Commons (BY-SA) license

My connected friend, Maha Bali, shared a post about thinking through how to navigate the world of citation in the age of ChatGPT and AI-generated text, particularly if a writer uses the AI chat for parts of their own writing and/or research. Maha suggested a citation format, but I was particularly intrigued by Alan Levine’s thoughtful response in the comments, and when Alan referenced Jonathan Portiz’ insights about how or whether to reference machines in the act of writing, using the use of music software for songwriting as an example, something perked up for me.

(See Maha’s post and the comments at the bottom and then her follow-up post)

I like to write and produce music, mostly at the hobby level. Although I do play real instruments (saxophone and rhythm guitar, and I also dabble with bass and keyboards), I also often turn to apps and platforms like Garageband and Soundtrap, and use sound loops and other elements of the computer to create music.

When I have shared those pieces out, I have often wrestled with how to make sure anyone listening (if anyone is even listening) would know it wasn’t me playing those instruments, but some musical loops. Often, of course, it’s obvious, mostly because the music comes out rather way too flawless and always exactly on the beat, like a droning metronome. That said, it’s not always obvious that technology has been used. If I am layering in my own singing voice, or my saxophone, or guitar into the mix, then the hybrid pieces are a bit of both things — the human musician and the algorithmic loops.

I have yet to come to a suitable system for letting anyone listening know that a piece of music is more computer loop than musician me. To be honest, I often travel the lazy route — no mentions of the software.

Here’s an example of what I mean. A music friend had sent me some lyrics and asked for a song, which I then built musically in Garageband after adding some lyrics to his words myself, so it’s a human-human-machine collaboration. When I shared the final version with him, he admired my guitar playing, to which I let him know the reality – none of it was me.

So this topic of leaning on the machine for creativity, and whether to make that kind of technical support more visible to others in any published content through citations or some other methods, has long been at the back of my mind.

This has been made more pertinent in recent years as my teenage son has been producing his own music tracks using another (more advanced) digital music software platform, collaborating with hiphop singers and writers from around the world. He doesn’t play an instrument. He plays the platform. He doesn’t cite the platform when he posts his music on the major streaming services.

Should he be considered a musician, even though he didn’t make any of the original loops himself? What about if he edits and changes the loops, as he does? Should every loop he uses be cited somehow?

All this brings us to ChatGPT and its brethren, and Maha’s exploration of how to make citations when using AI chat platforms for writing pieces.

Is it necessary to cite the machine?

My initial impulse is that Maha’s discussion about writing and citation feels different from making songs because it is writing of words through predictive text of the AI and not music composition with prerecorded loops. Writing a poem or a story or an essay also feels different than writing a song that layers words over music.

Even as I write that, though, I realize: that statement doesn’t seem to sit well with me at all — all are creative acts that begin with nothing but an idea and lead to something that others can experience. Maybe my conflicted feelings stem from being so used to technology being integrated so fully into the modern field of music production, and I am not yet used to its use in the field of writing.

Not yet, anyway. Will time and experience change that?

Garageband and Soundtrap and others don’t cite the musicians where the original loops came from. Do we expect that ChatGPT and others will cite where their words come scraped from? I believe that to be a strong yes in my view – that such information about original sources should be baked into the chart system (even as I understand the technical aspects will make such a thing nearly impossible). If this were done, then a writer could cite the sources of their AI-influenced writing.

Right? Hmm.

How confusing is all this? Pretty.

And how interesting to grapple with it? Very much so.

Peace (in the machine),

Reflecting On ChatGPT And The Teaching Of Writing

Chalk Talk ChatGPT Daily Hampshire Gazette

Like many educators, the arrival of ChatGPT has raised some of my alarm bells and also piqued my interest. I wrote about this, from a teaching perspective, for the local newspaper. Interestingly, it was written a few weeks ago, and even now, I find there are more wrinkles with the topic that could have made the piece better. Oh well.

Peace (with the Bots),

Movies On The Page: Internet Archive Remix

My DS106 friend, Paul B, shared a call from the Internet Archive, inviting people to use material from 1927 — now entering the Public Domain — for creative remix for a contest with cash awards. I sent the invite along to two of my sons who are filmmakers and then thought, What about me? (And what about you? See the Internet Archive blog post with all the information)

I dove in and came up with idea of using a 1927 periodical’s front page as a series of movie screens for clips from animated movies from the 1927 collection. I was hoping for something more narrative cohesive, but I ran out of time and patience and technical know-how.

I still like how the project came out, though, with little screens on the page, and clips from the movies showing. And the other entries coming into the contest are pretty cool. Check out the page where the projects are tagged.

Peace (and remix),

Playing Around With A Family of Arty-Bots

ArtyBots Remix Collage

I don’t remember how or when I stumbled upon the collection of Twitter bots by B.J. Best but I suspect it have been during one of the handful of Networked Narrative projects I engaged with (in one session, we all created our own bots and mine is still rolling along as the PeaceLove&Bot). The Artybots collection by Best, a poet and designer, are fascinating, particularly because they were released before this latest wave of AI Art platforms.

Here is my video collection of remixes from the ArtyBot Family:

You can learn more about his project in this podcast interview at Design Notes.

The way the ArtyBots work is that you tweet an image to the bot and then it generates an artistic response, using the original image as the base of its operations. Some of the bots are also programmed to respond to each other, connect within what he calls the Bot Family.

I decided to play with his various bots with a single image. I choose an image that was an interesting zoomed-in shot of some moss on a pavement curb. I then fed the image to the various bots, and took the results, pulling them together into the slideshow. Not all of his bots fed me back an image to use, for whatever reason, but I enjoy seeing the remixed images that did come back fade into one another in the video compilation.

Is this art? Are the computer programs artists? Who knows, anymore. (Best suggests yes, the bots are artists in his podcast interview).

Peace (and Bots),

Rusty, The Rock And Roll Robot: From AI Art to AI Story with AI Music

Maybe I went a little overboard here but I was curious about what would happen if I merged the output of a variety of different AI-infused sites to create an AI story from an AI image with a computer-generated narrator voice backed with an AI soundtrack. The result was a tale about Rusty the Guitar-playing, Rock-and-Roll Robot.

Here’s how it worked: This all began with an interactive article in the Washington Post about how AI engines create art from text prompts. The article is excellent and the tool to play with was worth tinkering with, so I used the prompt to guide my experiment along: A robot playing guitar in outer space in style of a cover of a magazine.

AI Art via WashPo

I had an interesting image that I downloaded but now wanted a story. So I opened up ChatGPT and typed in this prompt: Write a funny story of a robot making the cover of a magazine for playing guitar in outer space.

Within seconds, I had the text of a story about a robot named Rusty who was rocking the space jam and ending up going viral and landing on the cover of a magazine. I took a screenshot the story.

Story via ChatGPT

I went into LunaPic to merged the Art image with the story, and added a border. Neat.

AI Art Meets ChatBotGPT

Now I wanted some voice narration. I used a text-speech site that wasn’t AI, really, but the computer-generated voice worked for what I needed: a “narrator” reading the text of the story of Rusty as an audio file.

Knowing this would become a video project, I wanted some soundtrack music. I went into a site called Melobytes, which takes an image and used AI to convert it to music. I used the combined Rusty Art/Story from LunaPic, and got a soundtrack. (I remain a little skeptical and unsure of how Melobytes really works its AI magic, but I stayed with it because I could not find an alternative for this activity).

I also used Audacity to mix the music with the narration, and then went into SoundSlides to pull everything together into one project, with an image backed by audio.

Is it any good?

Well, it’s interesting as an experiment, I think, and it shows how more and more AI projects could become collaborations across platforms.

Is it writing?

I don’t think so, but it was an act of “composition” as I tried to weave different threads of the story, generated by machine, into a coherent media project.

And you know, it’s likely that some company will surely bring all of these AI tools — art, text, music — under one umbrella at some point, and I am not even sure if that is a good development or bad idea when it comes to the world of stories.

Peace (press Play),

ChatGPT: Alarm Bells And Learning Possibilities

ChatGPT Play Skit The Case of the Missing Jazz Song

First, it was Wikipedia that would be the end of student research. Then it was Google and other search engines that would be the end of student discovery and learning of facts and information. Now it might be ChatGPT that might be the end of student writing. Period.

As with the other predictions that didn’t quite pan out in the extreme but still had important reverberations across learning communities, this fear of Machine Learning Chat may not work itself out as extreme as the warnings already underway in teaching circles make it seem, but that doesn’t mean that educators don’t need to take notice about text-based Machine Learning systems, a technology innovation that is becoming increasingly more powerful and user-friendly and ubiquitous.

For sure, educators need to think deeply about what we may need to do to change, adapt and alter the ways we teach our young writers what writing is, fundamentally, and how writing gets created, and why. If students can just pop a teacher prompt into an Machine Learning-infused Chat Engine and get an essay or poem or story spit out in seconds, then we need to consider about what we would like our learners to be doing when the screen is so powerful. And the answer to that query — about what can our students do that machine learning can’t — could ultimately strengthen the educational system we are part of.

ChatGPT: Write A Sonnet

Like many, I’ve been playing with the new ChatGPT from OpenAI since it was released a few weeks ago. As I understand it (and I don’t, really, at any deep technical level), it’s an computational engine that uses predictive text from a massive database of text. Ask it a question and it quickly answers it. Ask for a story and it writes it. Ask for a poem or a play (See my skit at the top of the page) or an essay, or even lines of computer code — it will generate it.

ChatGPT: Literary Analysis Paragraph

It’s not always correct (The Lightning Thief response looks good but has lots of errors related to a reading of the text itself) but the program is impressive in its own imperfect ways, including that it had access to the Rick Riordan story series in its database to draw upon. And, as powerful as it is, this current version of ChatGPT may already be out of date, as I think the next version of it is in development (according to the hosts at Hard Fork), and the next iteration will be much faster, much larger in terms of scale of its database, and much “smarter” in its responses.

Can you imagine a student taking a teacher prompt assignment and putting it into the Chat engine, and then using the text as their own as classroom submission? Maybe. Probably. Will that be plagiarism? Maybe.

Or could a student “collaborate” with the Chat engine, using the generative text as a starting point for some deeper kind of textual writing? Maybe. Probably. Could they use it for revision help for a text they have written? Maybe. Probably. Right now, I found, it flattens the voice of the writing.

ChatGPT: Revise This Text

Could ChatGPT eventually replace the need for teachers? Maybe, although I doubt it (or is that just a human response?)

But, for educators, it will mean another reckoning anyway. Machine Learning-generated chat will force us to reconsider our standard writing assignments, and reflect on what we expect our students to be doing when they writing. It may mean we will no longer be able to rely on what we used to do or have always done. We may have to tap into more creative inquiry for students, something we should be doing anyway. More personal work. More nuanced compositions. More collaborations. More multimedia pieces, where writing and image and video and audio and more work in tandem, together, for a singular message. The bot can’t do that (eh, not yet, anyway, but there is the DALL-E art bot and there’s a music/audio bot under development and probably more that I don’t know about.)

Curious about all this, I’ve been reading the work of folks like Eric Curts, of the Control Alt Achieve blog, who used the ChatGPT as collaborator to make his blog post about the Chat’s possibilities and downsides. I’ve been listening to podcasts like Hard Fork to get a deeper sense of the shift and fissures now underway, and how maybe AI Chats will replace web browser search engines entirely (or not). I’ve been reading pieces in the New York Times and the Washington Post and articles signalling the beginning of the end of high school English classes. I’m reading critical pieces, too, noting how all the attention on these systems takes away from the focus on critical teaching skills and students in need (and as this post did, remind me that Machine Learning systems are different from AI)

And I’ve been diving deeper into playing more with ChatGPT with fellow National Writing Project friends, exploring what the bot does when we post assignments, and what it does when we ask it to be creative, and how to try push it all a bit further to figure out possibilities. (Join is in the NWPStudio, if you want to be part of the Deep Dive explorations)

Yeah, none of know really what we’re doing, yet, and maybe we’re just feeding the AI bot more information to use against us. Nor do we have a clear sense of where it is all going in the days ahead, but many of us in education and the teaching of writing intuitively understand we need to pay attention to this technology development, and if you are not yet doing that, you might want to start.

It’s going to be important.

Peace (keeping it humanized),

Making A Video Haiku With An AI Collaborator

I saw in my RSS feed that Eric Curtis, whose sharing of technology resources is always fantastic and useful, had mentioned that Canva had just launched a Text-Image AI tool, in which you feed it some words and it generates some images. This image generation feature has become a fairly common feature of AI these days, but I was still curious about how to use it within the platform of Canva (which has a slew of useful design tools and options).

Since this tool is still in beta (I believe), the link is not within the main Canva toolbox quite yet, so this is how you access it: https://canva.me/text-to-image

I grabbed a haiku I had written earlier in the say (off a prompt via Mastodon, with the word “mist” as a key inspiration) and fed it into the Canva tool. Full phrases were less useful than key words, I found, but the images were quite dreamy and evocative (I chose a “painting” setting in the tool).

I played with the Canva video maker tool, weaving the words of the original haiku through the video slides with the AI images, and choosing a piece of music (all within Canva itself) to create the short video poem. I utilized some other design features inside Canva, too, but the images were all AI-generated. It’s still strange to have AI as your creative partner in these things, but it’s interesting, too, to see where AI might offer up useful ideas or not.

To see how it works, read through Eric’s post. It is very detailed and helpful.

Peace (and AI),