Standard 3 stops to get here · leads to 2
Audio Processing
Techniques for analyzing, transforming, and understanding audio signals for tasks like speech recognition and music generation.
Your route here
3 stops · basics first
- Dataset ✓ understood
A collection of data examples used for training, validating, or testing machine learning models.
- Feature ✓ understood
A single measurable property of an example, such as a house's floor area or how many links an email contains, used as an input to a model.
- Feature Engineering ✓ understood
The process of selecting, transforming, and creating input features to improve model performance.
- Audio Processing · you are here ✓ understood
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Language & LLMs Speech Recognition Converting spoken language into text using acoustic models and language models, now dominated by deep learning. Vision & Multimodal Text-to-Speech Synthesizing natural-sounding speech from text, using neural vocoders and attention-based models. Neural Networks Convolutional Neural Network A neural network that scans images with small learned filters, reusing the same weights at every position to build up from edges to whole objects. Vision & Multimodal Multimodal Model Models processing multiple data types (text, images, audio) jointly, like GPT-4V, Gemini, or CLIP.