Terminology

1. Audio Source Separation - Source separation techniques in audio processing can be classified into various methods, such as blind source separation, supervised source separation, and semi-supervised source separation. These techniques use algorithms and signal processing methods to extract specific sound sources from an audio mixture. It can be classified into various methods, such as blind source separation, supervised source separation, and semi-supervised source separation. (note: Usually these methods are for multi-channel. If we have a single channel audio recordings, this is more challenging.)

2. Sound event detection - Sound Event Detection (SED) is the task of recognizing the sound events and their respective temporal start and end time in a recording. Sound events in real life do not always occur in isolation, but tend to considerably overlap with each other. Recognizing such overlapping sound events is referred as polyphonic SED.

3. Query-based separation - Query-based separation in audio could involve using specific sounds or queries to identify and extract particular sounds from an audio recording. For example, in a crowded audio environment, you might use query-based separation to extract the voice of a specific speaker from a mixture of voices. By providing a query related to the speaker's voice characteristics or specific phrases they are saying, algorithms can be designed to identify and separate that particular speaker's voice from the overall audio recording.