What is Digital Signal Processing (DSP)?
Digital Signal Processing is the mathematical and algorithmic manipulation of audio (and other) signals to analyze, enhance, or transform them. It's the foundation beneath speech recognition, TTS, noise reduction, and every modern voice AI system.
What is an example of Digital Signal Processing?
Applying a high-pass filter to remove low-frequency rumble or running echo cancellation on a phone call are DSP operations.
How does Digital Signal Processing work?
DSP operates on digital audio — sequences of samples — using techniques like filtering, convolution, and adaptive algorithms. These can be implemented as fixed pipelines or fused with neural networks, which is how most modern speech enhancement systems are built.
How does ai-coustics use Digital Signal Processing (DSP)?
Our speech enhancement models are a hybrid of deep learning and DSP. Signal-level operations provide the structure that our neural networks act on. Combined with our AirTen inference engine, this lets Quail and Rook run at low latency on CPU, processing many concurrent streams for real-time voice AI.
