Abstract: In this work, we propose CleanMel, a single-channel Mel-spectrogram denoising and dereverberation network for improving both speech quality and automatic speech recognition (ASR) performance ...

This issue has been somewhat brought up in another post, but I also wanted to point out that the scipy.spectrogram function used in compute_spectrum_welch is now considered a legacy function. There's ...

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 ...

Over the past few decades, animal sounds have seen a huge surge in research. Advances in recording equipment and analysis techniques have driven new insights into animal behaviour, population ...

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.

Identifying 5G NR and LTE signal via spectrum sensing using deep-learning techniques. How to characterize spectrum occupancy by training a neural network. Testing network signal identification ...

Tutorials play a crucial role in learning new skills, from software development to cooking, and everything in between. In this day and age, tutorials can be found in various formats, such as blog ...

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 ...