Robust voice activity detection (VAD) is a challenging task in low signal-to-noise (SNR)
environments. Recent studies show that speech enhancement is helpful to VAD, but the …

Although recent advances in deep learning technology improved automatic speech
recognition (ASR), it remains difficult to recognize speech when it overlaps other people's …

Robustness against background noise and reverberation is essential for many real-world
speech-based applications. One way to achieve this robustness is to employ a speech …

Voice activity detection (VAD) is considered as a solved problem in noise-free condition, but
it is still a challenging task in low signal-to-noise ratio (SNR) noisy conditions. Intuitively …

Transfer learning is a promising approach to increase performance for many speech-based
systems, including voice activity detection (VAD). Domain adaptation, a subfield of transfer …

在许多语音信号处理的实际应用中, 都要求系统能够低延迟地实时处理多个任务,
并且对噪声要有很强的鲁棒性. 针对上述问题, 提出了一种语音增强和语音活动检测(Voice …

Magnitude and phase aware deep neural network (MP-aware DNN) based on Fast Fourier
Transform information, has recently received more attention in many speech applications …

In real-world scenarios, speech signals are often contaminated with environmental noises,
and reverberation, which degrades speech quality and intelligibility. Lately, the development …