🔍 Introduction You’ve probably heard how AI models can recognize accents, emotions, or even impersonations. But how does a machine see sound? In this post, we’ll use MFCCs—Mel-Frequency Cepstral Coefficients—to compare two audio signals side by side...
Speech is one of the most complex and information-rich signals in the world. From human communication to AI-powered virtual assistants like Alexa and Siri, speech processing plays a crucial role in various applications, including: ✅ Speech Recognitio...
When working with speech processing, the first thing that comes to mind is the waveform—a raw representation of sound amplitude over time. But is waveform always the best choice? Advanced speech signal representations offer better clarity, feature ex...
Speech processing is a critical part of AI and Audio Technologies. In this article, we’ll explore fundamental techniques used for speech feature extraction: Fourier Transform & Spectrograms (Visualizing speech in the frequency domain) Mel-Frequency...
1. Introduction In the field of speech processing, converting continuous signals into a form that can be processed by machines is crucial. This digital representation of speech involves three fundamental concepts: waveforms, sampling, and quantizatio...