The phrase "audio separation" is correct and usable in written English.
It can be used in contexts related to sound engineering, music production, or audio processing, referring to the process of isolating different audio elements from a mixed track.
Example: "The software offers advanced audio separation features that allow users to extract vocals from a music track."
Alternatives: "sound isolation" or "audio extraction".
The "privacy" this system will provide is open to interpretation: an assortment of ethereal cotton-spandex screens that flex like wings can be snapped in place to offer some semblance of visual and audio separation.
The quality of the audio separation using different frame sizes N, time shifts J and maxIter iterations is evaluated in preliminary studies.
However, for speech and audio separation problems in real-world acoustic environment, such as the "cocktail party problem", signals are often mixed in a convolutive manner.
For audio separation [10, 11] and recognition [12, 13] tasks, the time and frequency analysis is usually implemented using well designed filter banks.
In [19], an online IVA algorithm was proposed for real-time audio separation task, and a two-channel hardware demonstration system was developed.
Since BSS and ICA have many successful applications in speech and audio separation tasks, a natural choice is to use these techniques to perform train noise component separation; however, noise signals from mechanical vibration are very different from speech.
Finally, after estimating the mixing matrix, we used the flexible audio source separation toolbox (FASST) [38] to separate the sources.
The use of simulated data is widespread in audio source separation and it has been shown to yield comparable separation performance to real-world data in general [37].
Using these representations, we demonstrate the impact for low-shot visual recognition and visually-guided audio source separation.
In addition, we introduce and evaluate five new TDOA estimation methods inspired from signal-to-noise-ratio (SNR) weighting and probabilistic multi-source modeling techniques that have been successful for anechoic TDOA estimation and audio source separation.
a The NN structure for audio source separation task.
