Tag: sound

Fourth track for Noisevember! I learned several things about working with FFTs today, but I didn't use them on this track...This track started with another field recording of crows I made, and then I manipulated it using so techniques I've made use of in the past, just to get warmed up, as it were. It's noisy but nice!

Listen!

Tracks 2 and 3 for Noisevember.

Track 2 is a short piece made using a recursive composition method that I've been playing with for a while. It's hard to control, so I keep trying. Made with Csound with a score I generated with some code I wrote in Python.

https://soundcloud.com/matthew-m-conroy/recursive-composition-a

Track 3 is a manipulation of a field recording of crows I made a while back. The manipulation is a bunch of different simple shifts of the spectrum using FFTs. I'm really trying to understand how to use FFTs better!

https://soundcloud.com/matthew-m-conroy/crows-shifted

My first track for Noisevember 2026. This month, I intend to experiment with reverb and vocoder-like things. This track uses a convolution reverb with an impulse I made with some Python code, and FFT-based vocoder-type manipulations done in Python. The audio source is one of my favorite films, The Petrified Forest, with Bette Davis and Lesley Howard.

Listen.

I added a new page to my website.

On it are plots of the roots of all the polynomials in certain sets arising from a given polynomial, P, by taking each coefficient of P and multiplying it by 1 or -1 to create a new polynomial. The plots are all roots of all polynomials generated in this was from a given P. The first is where all of the coefficients of P are 1, so the set of polynomials generated are Littlewood polynomials.

In addition to the plots, I generated sound for each one by treating each root as a sound event. Time runs "right to left" (so the real part of the root determines when its sound event occurs) and the pitch (frequency) is determined (linearly) by the imaginary part of the root. The result is a sound whose spectrogram looks like the plot of the roots.

The range of real parts varies, so the duration of the sounds varies. The extreme case is where the coefficients of P are the factorials of the degree; with such huge coefficients, the roots are quite small, and the result is that the sound is quite short.

A new track. I've been posting something every day on Soundcloud, but I really like this one I made today. I used a piece of a field recording I did that includes a trombone and an escalator. This track is entirely in the spirit of tape music: though done digitally, it could, theoretically be done entirely with tape (with many, many, many splices). I hope you enjoy it! https://soundcloud.com/matthew-m-conroy/trombonscalator

I've started making audio pieces for Noisevember. They are, so far, all in my playlist on soundcloud, here: https://soundcloud.com/matthew-m-conroy/sets/noisevember-2025

I'm having fun!

Part of some sound experiments. Here, I played a tin whistle and modified the sound, live, with a Csound instrument that has delayed copies of the signal interfere with each other spectrally. No oscillators.

listen on soundcloud

I just released a new video piece. I called it INK because there's a lot of ink in the video and "Ink" looks so small. Sounds composed with Csound using a python script I wrote to analyze the individual frames of the video. A big screen is recommended (I use the Vimeo app on an Apple TV to watch my videos on my television).

INK from Matthew Conroy on Vimeo.

I finished my EP for the RPM Challenge 2024.

I had a lot of fun with it: I think I had more time to spend on it this month than in many recent Februaries.

I put it on Soundcloud and Bandcamp. Let me know what you think!

A piece for Disquiet Junto 0607 .

My thoughts went like this.

We cannot be 40% silent at a single point in time, so we have to define the amount of silence at a point in terms of the sound that is happening around that point. I chose to define the percentage of silence at a point in time as the percentage of silence (time with zero amplitude) in a 14 second interval centered at that point in time.

Also, it seems to me that we do not actually hear silence unless it is of sufficient length (e.g., we do not hear “silence” when there is a 0.001 second gap in a sound). For this piece, I defined silence to be an interval of at least 0.5 seconds of zero amplitude. I could see an argument for requiring longer gaps than this, though, since with short “silences”, I feel that we are still hearing the sound that came before it, and not actually hearing the silence.

So then I randomly threw 25000 sound events onto a 5 minute span of silence, checking before each one that the percentage of sound at that point would not go above that required by the instructions (i.e., a linear increase from 0 to 40% sound at the midpoint and linearly back to zero for the second half).

The sound events are guitar samples I’ve made, pitched and filtered in various ways. There are many points where the samples “pile up” and make a noticeably louder occurrence; this happens because once a sound has been placed, another sound can be placed “on top” of it, with no reduction in the amount of silence.

It was fun coding this, and I’ve grown to like the result after numerous tweeks and re-listens.