In this paper, we investigate multi-stream acoustic modelling using the raw real and
imaginary parts of the Fourier transform of speech signals. Using the raw magnitude …

As the fast development of wearable devices and Internet of things technologies, real-time
monitoring of ECG signals is quite critical for cardiovascular diseases. However, dynamic …

In recent years, radar automatic target recognition (RATR) utilizing high-resolution range
profiles (HRRPs) has received significant attention. Approaches based on deep learning …

Commonly used features in spoken language identification (LID), such as mel-spectrogram
or MFCC, lose high-frequency information due to windowing. The loss further increases for …

(1) Background: Voiceprint recognition technology uses individual vocal characteristics for
identity authentication and faces many challenges in cross-scenario applications. The sound …

Speech recognition technology is an important branch in the field of artificial intelligence,
aiming to transform human speech into computer-readable text information. However …

We study the problem of learning robust acoustic models in adverse environments,
characterized by a significant mismatch between training and test conditions. This problem …

We investigate the potential of stochastic neural networks for learning effective waveform-
based acoustic models. The waveform-based setting, inherent to fully end-to-end speech …

Joint training of speech enhancement model (SE) and speech recognition model (ASR) is a
common solution for robust ASR in noisy environments. SE focuses on improving the …

Extracting noise-robust features is a key issue for high-resolution range profile (HRRP)
target recognition. In order to enhance the recognition performance under low signal-to …