Recently, mainstream mel-spectrogram-based neural vocoders rely on generative adversarial network (GAN) for high-fidelity speech generation, e.g., HiFi-GAN and BigVGAN. However, the use of GAN ...

Creating an issue in case my comment at the closed PR #9527 falls through the cracks. I just updated SE to 4.0.12, and I'm afraid the new merged waveform + spectrogram is not workable for me. As you ...

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 ...

Soundscape analysis has become integral to environmental monitoring, particularly in marine and terrestrial settings. Fish choruses within marine ecosystems provide essential descriptors for ...

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.

Abstract: It is challenging to deploy Transformer-based audio classification models on common terminal devices in real situations due to their high computational costs, increasing the importance of ...

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 ...

LASS or Language-queried Audio Source Separation is the new paradigm for CASA or Computational Auditory Scene Analysis that aims to separate a target sound from a given mixture of audio using a ...