SlowWave
SlowWave is a creative slow-playback and reverb transformation tool that lets you stretch audio between 0.5x and 1.5x while shaping ambience with size and mix controls. It includes LR peak meters, stereo correlation, and dual-layer […]
Balance 5
Balance 5 is a high-precision 5-band parametric equalizer designed for accurate tonal balancing, critical listening, and real-time visual feedback. The standalone version allows you to load and analyse audio files without the need for a […]
Spectra 99
SPECTRA 99 is designed for modern high-definition audio workflows and is fully optimized for sample rates up to 96 kHz, delivering precise and stable spectral analysis in both standard and high-resolution sessions. The standalone application […]
Audio AI Reading Notes
A curated list of papers and articles I’ve read recently, focused on neural audio, DSP, and music AI. Each entry includes the original source and my key takeaways. This page is being updated regularly. More […]
Transformer For Denoising
Although small datasets make denoising a challenging task, this experiment shows how transformer models can handle audio cleaning in a practical way. The idea is simple: can we teach a transformer — originally built for […]
Composing Without a DAW
Lately, I’ve been exploring ways to handle everything — notation, MIDI tweaks, and VST instruments — without switching to a DAW. Even with the free version of Dorico from Steinberg, I was surprised by how […]
Optimizer Comparision
Choosing the right optimizer is essential when training neural networks, especially for audio tasks like denoising or filter tuning. The optimizer controls how model parameters are updated, affecting convergence speed, stability, and final performance. A […]
SNR Maximization and Wiener Filtering
In digital audio processing, one of the most common tasks is reducing background noise while keeping the original signal as clear as possible. This balance is typically expressed as maximizing the Signal-to-Noise Ratio (SNR) — […]
Supervised Audio Denoising
What is a Supervised Model? A supervised model is a type of machine learning algorithm that learns to map inputs to known outputs using labelled data. The context of audio denoising consists of noisy audio […]
Cosine Similarity
Recently, I experimented with a quick way to measure how similar two audio tracks are — not by comparing raw waveforms, but by looking at their spectral patterns. Using PyTorch and Torchaudio, I load two […]
Denoising with Rectified Flow Models
This project trains a 1D convolutional neural network with time embeddings to remove noise from audio, inspired by Rectified Flow Models (RFM). What is a Rectified Flow Model? An RFM learns a velocity field that […]
HRTF Spatialization: Mono to Stereo
I took a plain mono audio file and transformed it into a stereo track that sounds like it’s coming from a real direction in space — using HRTF data from a SOFA file. HRTF (Head-Related […]
Neural Audio Fingerprinting
This is a basic implementation of neural audio fingerprinting using PyTorch and torchaudio. It serves as a solid foundation for tasks like music identification, audio search, and deep audio retrieval. CNN architecture, sample rate, and […]
Simple RNN for Speech Denoising
I recently built a lightweight speech denoiser using a GRU-based recurrent neural network that operates directly on raw audio frames. What I did: Implemented a SimpleDenoiserRNN with a single GRU layer and a linear output […]
Neural Audio Codec
This is a basic neural audio codec implementation using a convolutional encoder and decoder, along with a quantizer. The encoder compresses raw audio into a low-dimensional latent vector. A simple scalar quantizer then rounds the […]
Arc-Length-Based Sampling in Latent Space
Here, I morph between two points (A to B), through an optional control point, and compare arc-length based sampling to linear interpolation. Main idea comes from my implementation for curve point distribution in 2D latent […]
Pretrained Mono CNN in JUCE Plugin
—*Testing Stage* — I tried adding a pretrained mono CNN into a JUCE plugin to experiment with real-time audio processing, mainly thinking about a vocal denoiser. The process turned out simpler than I expected, and […]
Local Extremas and Nesterov Accelerated Gradient
To find a global minimum for a selected function, I compared brute force sweeping with Nesterov Accelerated Gradient (NAG) optimisation technique. By applying a small deltaX increments, I obtained local extremas in the range of […]
Arc Length by Simpson’s Rule
Simpson’s Rule is a classical numerical integration technique used to approximate definite integrals, especially when the integrand is difficult or impossible to integrate analytically. While it is a fundamental tool in numerical analysis and calculus, […]
Data Augmentation for MIDI: Transposing
One of data augmentation techniques for music dataset is transposing. In my opinion, it is quite useful for OMR training – image to notation process (score to music notation) like stem directions and clusters. However, […]
1 2 ›