Abstract: The spectrogram is a useful tool for the time-frequency analysis of non stationary signals. This tool, however, is based upon a multicomponent sinusoidal model over a signal analysis frame ...

Signal analysis and classification is fraught with high levels of noise and perturbation. Computer-vision-based deep learning models applied to spectrograms have proven useful in the field of signal ...

Benjamin A. Jancovich's work is funded by the Australian government's Research Training Program. In a new study published in Ecology and Evolution, we show the limitations of one of the most common ...

The radio hackers in the audience will be familiar with a spectrogram display, but for the uninitiated, it’s basically a visual representation of how a range of frequencies are changing with time.

Add a description, image, and links to the spectrogram-transformer topic page so that developers can more easily learn about it.

Abstract: Since a frequency modulation signal can be approximated by polynomial chirplet in a local time window, polynomial chirplet transform has been applied to acoustic signal processing, radar ...

Speech continuation and question-answering LLMs are versatile tools that can be applied to a wide array of tasks and industries, making them valuable for enhancing productivity, improving user ...

For the task of speech separation, previous study usually treats multi-channel and single-channel scenarios as two research tracks with specialized solutions developed respectively. Instead, we ...