Unveiling Hidden Structures: A Deep Dive into Gaussian Mixture Models In the world of data science, we often encounter datasets that don’t neatly fit into a single, simple distribution. Imagine trying to model the heights of all adults in a country – you’d likely see two peaks, one for men and one for women. How … Read more
In the ever-evolving landscape of modern technology, electromagnetics plays a ubiquitous role, from medical imaging to remote sensing. Understanding how light interacts with various objects and materials is fundamental to diverse fields, but traditional methods for solving electromagnetic scattering problems often demand high-performance computing due to complex geometries or large dimensions. However, my Thesis work … Read more
Unlocking the Spoken Word: A Deep Dive into Automatic Speech Recognition (ASR) in the Fearless Steps Project In our increasingly connected world, human-machine interactions through speech have become a cornerstone of modern technology. To elevate these interactions, extracting meaningful information from audio signals is crucial, and that’s where speech processing steps in. The “From SAD … Read more
Unmasking Voices: A Deep Dive into Speaker Identity Detection (SID) in the Fearless Steps Project In the exciting world of human-machine interactions, speech processing is paramount for extracting meaningful information from audio signals. The “From SAD to ASR on the Fearless Steps Data” project, conducted by researchers at Paderborn University, takes a significant leap in … Read more
The Silent Revolution: Precisely Pinpointing Speech in Audio In our increasingly voice-driven world, from virtual assistants to smart home devices and automated call centers, understanding when someone is actually speaking is paramount. This seemingly simple task is the domain of Speech Activity Detection (SAD) – the crucial ability to accurately differentiate between speech and non-speech … Read more
In linear regression, Ordinary Least Squares (OLS) is a powerful method for finding the best-fit line for a dataset. Its primary appeal is that it offers a closed-form solution, meaning you can calculate the ideal model parameters in a single step using matrix operations, rather than through an iterative process. To the notebook in Github The OLS Approach … Read more
Signal processing is a fascinating field that allows us to synthesize, transform, and analyze signals, with a particular focus on sound. In our modern digital world, converting continuous analog sound into discrete digital data is a crucial first step for many applications, from streaming music to speech recognition systems. This process is known as sampling, … Read more
Have you ever wondered how machine learning algorithms can both categorise data and simplify complex datasets without losing crucial information? Meet Linear Discriminant Analysis (LDA), a powerful technique that does exactly that. Often seen as a foundational method, LDA plays a dual role in both classification and dimensionality reduction. LDA: More Than Just a Classifier … Read more
Understanding how signals behave in the frequency domain is crucial for engineers working with digital speech. The Fourier Transform is our most powerful tool for this, allowing us to decompose complex signals into their constituent frequencies. Let’s embark on a step-by-step journey through its various forms, with a particular focus on accurate mathematical representation: the … Read more