TI-99 speech effect? - audio

I want to make a program that takes recorded speech and transforms it so it sounds like it's coming from a Texas TI-99. Do you have any good ideas and resources for how to go about that?

Most of those old speech synthesizers were build directly in-chip. Perhaps you could find a synthesizer that sounds like the chip, but if you really want the original sound, you would either have to simulate the chip (I don't know if it's a simple matter, perhaps the chip internals aren't published).
I only know because I burnt out a number of the Radio Shack speech synthesizer ICs before I managed to get a SP0256-AL2 working.
If you're more of a do-it yourself type guy, you need to find out which IC actually drove the speech synthesis in a TI-99, and then build the chip up on a bread board. That's what I was trying to do back then, and I managed to get the chip to speak, but lost patience after I fried my third chip due to a mis-wiring issue when I attempted to attach it to my PC's parallel port. I think this was the book I was using back then, but there's no cover art featured so it's hard to know for sure.
If you are familiar with how to use ROM images, there seems to be a gentleman that has managed to refeverse engineer the ROM image out of a SP0256-AL2. Look here for the image and the incredible granted permission to do the work and distribute the results.

You could start with open source that does something similar: Adding Robotic/Vocoder effect to your song using Audacity

Related

Detect different speakers in an audio recording

I want to make an application that counts the speaking time of each speaker in an audio recording. I don't care about doing full voice recognition and transcribing every word in the recording, I just want the speaking time of each voice.
Is there a piece of software that provides such feature?
If possible, I would like to avoid using a third-party service (such as Google Cloud) to achieve this, and I would like the solution to be light enough to run on a modern smartphone.
Thank you for your help.
I had the same idea. Check this out https://github.com/pyannote/pyannote-audio
Haven't tried it myself yet. Will add an edit after.

APCS final project: Converting an audio file to a simpler MIDI file

Lets say I have the audio file for Happy Birthday. I want to convert that audio file into an audio file that sounds like this : happy birthday.
First, I'd like to know if I have the ability to program this? Can a highschooler who's almost finished with APCS program this?
If I can:
How would I change the bpm of the song? I've searched through a bunch of websites, but they weren't very helpful.
I know that audio files can be represented in waveforms. How would I scan for each individual wave in an audio file (I need this to isolate the notes)?
This is a very ambitious project, actually. One reason is that it involves using digital signal processing tools like FFT (Fast fourier transforms) to analyze the sound to pick out the pitches. You might be able to find a library that can do this, but as far as coding such a tool, that would involve a steep learning curve.
If you would like to look further into this, there is a good online resource called "The Scientists and Engineers Guide to Digital Signal Processing". I was able to work through and understand the discrete fourier transform with only high school math (lots of trig) and a bit of calculus. It was a lift, though.
Trying to analyze rhythm is also no easy task. Even with advanced tools provided in professional notation system such as Finale, people have trouble playing rhythms in time well enough for the best transcription tools. Algorithms that "quantize" the beats help but also limit the amount of detail that can be included in the playback.
My guess is that as interesting and worthwhile as this project would be, to bring it to completion before the semester ends would require putting together prebuilt pieces. A lot of programming is done that way, these days.
If you scale the project back to something like just getting your code to analyze a short sample of a single note and give its pitch, that would be both impressive and doable with a lot of work. It could be done with a DFT algorithm instead of requiring FFT, reducing the amount of info you'd have to acquire first. That way, you'd only have to work your way up to understanding and implementing the material on this link which is about calculating the DFT. Notice that there is example code in BASIC. The code examples throughout this book are a big help.

Passive and automatic face recognition

Hy guys. At school we use badge for mark who is present, for my exam i want to upgrade that system.
I would like to create a face recognition system, basically i would like to set a raspberry with camera over the doors, like that, when students pass the door will be automatically marked as present.
I know OpenBR but i didn't understand if i can use it for my project, and i have some issues with it, i can't install it, it return me an error when i test it.
I ask you if you know if OpenBR can do the trick for me (you have to know that we are a lot at school), or if there are some other technologies that i can use.
You could look at using opencv to train an object detector to look for the badge:
http://docs.opencv.org/2.4/doc/user_guide/ug_traincascade.html
https://www.youtube.com/watch?v=WEzm7L5zoZE
If each of the badges have some unique identifier for the students, you could then analyse the identifier to take attendance.
Identifying the badge / face would be the "easy" part. Identifying the student would be the hard part!
Identifying people from photos is tricky, and I would estimate that Facebook has spent millions on this problem.
Here are a couple of links that may be useful
http://scikit-learn.sourceforge.net/0.6/auto_examples/applications/plot_face_recognition.html
OpenCV identify person with face detection
You use Raspberry Pi for your project, so
Software:
1.OpenCV-Python is a very good choice.
2. SimpleCV is more simple to use but less power than OpenCV. It's still ok for your purpose.
Hardware:
You also need to be aware of hardware, using USB Webcam is not a good choice because of slow speed.
Module camera is better because it uses serial interface to transfer data.

Realtime audio manipulation

Here is what i like to achieve:
I like to play around in creating "new" software / hardware instruments.
Sound processing and creation is always managed by software. But one could play the instrument via ultrasonic distance sensor for example. Another idea is to start playback when someone interrupts the light of a photoelectric barrier and so on....
So the instrument would play common sounds, but has to be used in an unusal way. For example, the ultrasonic instrument would play a sound if it detects something in a certain distance. The sound could be manipiulated in pitch for example if the distance gets smaller.
Basically i like to playback a sound sample and manipualte this in realtime.
I guess i have to use WAV samples for this, right? And which programming language do you think fits best for this task?
Edited after kevins hint: please kick me into the right direction - give me a hint where to start.
Thanks in advance
Since you're using the the Processing tag, you can try Processing.
It comes with a sound library like Minim or you can install beads which is great. There's actually a nice book on it: Sonifying Processing
You might find SuperColider fun as well.
The main thing is what are you comfortable with at the moment ?
If Processing syntax looks intimidating, you can actually try a different programming paradigm like data flow. In which case you can use PureData(free, opensource) or MaxMSP(very similar, but commercial). The idea is rather than typing instructions, you connect boxes with wires which is fun and the examples are great too.
If you're into c++ there are plenty of libraries. On the creative side, there's a nice set of libraries called OpenFrameworks that's easy and fun to use. If this is your cup of tea, have a peek at Maximilian.
Bottomline is: there are multiple options to achieve the same task. Choose the best tool for your (based on your background) or try each and see what you like best.
You asked "And which programming language do you think fits best for this task?" - I would also suggest using Processing. I have been used Processing to work with sounds previously. And in all cases I used Minim. It has many UgenS to generate sounds programmatically.
Also, you wants to integrate with some sensors. I'm not sure what types of sensors you will use, but Processing goes pretty well with different Arduino modules and sensors. Check this link for more direction.
Furthermore, you can export your project as .exe or executable .jar files. And their JS version (P5.js) works almost the same as the Java version.

Recording the Stereo Mix and Parasites

I'm trying to make a video tutorial, so i decided to record the speeches using a TTS online service.
I use Audacity to capture the sound, and the sound was clear !
After dinning, i wanted to finish the last speeches, but the sound wasn't the same anymore, there is a background noise(parasite) which is disturbing, i removed it with Audacity, but despite this, the voice isn't the same ...
You can see here the difference between the soundtrack of the same speech before and after the occurrence of the problem.
The codec used by the stereo mix peripheral is "IDT High Definition Codec".
Thank you.
Perhaps some cable or plug got loose? Do check for this!
If you are using really cheap gear (built-in soundcard and the likes) it might very well also be a problem of electrical interference, anything from ...
Switching on some device emitting a electro magnetic field (e.g. another monitor close by)
Repositioning electrical devices on your desk
Changes in CPU load on your computer (yes i'm serious!)
... could very well cause some kinds of noises with low-fi sound hardware.
Generally, if you need help on audio sounding wrong make sure that you provide a way to LISTEN to the files, not just a visual representation.
Also in your posted waveform graphics i can see that the latter signal is more compressed, which may point to some kind of automated levelling going on somewhere in the audio chain.

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