Time Series/Audio/Speech Processing is a specialized field in computer science and signal processing that focuses on analyzing, manipulating, and extracting useful information from time-varying signals such as audio and speech data. It involves developing algorithms and techniques to process and understand the temporal patterns and characteristics of these signals. Time series analysis enables researchers to model and forecast future trends, detect anomalies, and extract meaningful insights from sequential data. In audio and speech processing, algorithms are designed to analyze and interpret audio signals, including speech recognition, speaker identification, emotion recognition, and sound classification. For example, in automatic speech recognition systems, time series/audio/speech processing techniques are employed to convert spoken language into written text, enabling applications like voice assistants, transcription services, and voice-controlled devices. These techniques involve tasks such as feature extraction, acoustic modeling, language modeling, and decoding to accurately transcribe spoken words into text.
| Source | Course Code | Course Name | Session | Difficulty | URL |
|---|---|---|---|---|---|
| Hugging Face | Audio Processing | ⭐ | Link (Free) | ||
| The State Unversity of New York | Practical Time Series Analysis | ⭐⭐ | Coursera |