Voice activity detection. fundamentals and speech recognition system robustness
An important drawback affecting most of the speech processing systems is the
environmental noise and its harmful effect on the system performance. Examples of such …
environmental noise and its harmful effect on the system performance. Examples of such …
Statistical voice activity detection using a multiple observation likelihood ratio test
Currently, there are technology barriers inhibiting speech processing systems that work in
extremely noisy conditions from meeting the demands of modern applications. This letter …
extremely noisy conditions from meeting the demands of modern applications. This letter …
Single frequency filtering approach for discriminating speech and nonspeech
G Aneeja, B Yegnanarayana - IEEE/ACM Transactions on …, 2015 - ieeexplore.ieee.org
In this paper, a signal processing approach is proposed for speech/nonspeech
discrimination. The approach is based on single frequency filtering (SFF), where the …
discrimination. The approach is based on single frequency filtering (SFF), where the …
Voice activity detection based on an unsupervised learning framework
How to construct models for speech/nonspeech discrimination is a crucial point for voice
activity detectors (VADs). Semi-supervised learning is the most popular way for model …
activity detectors (VADs). Semi-supervised learning is the most popular way for model …
[PDF][PDF] Boosted deep neural networks and multi-resolution cochleagram features for voice activity detection
Voice activity detection (VAD) is an important frontend of many speech processing systems.
In this paper, we describe a new VAD algorithm based on boosted deep neural networks …
In this paper, we describe a new VAD algorithm based on boosted deep neural networks …
[HTML][HTML] Multi-task learning u-net for single-channel speech enhancement and mask-based voice activity detection
In this paper, a multi-task learning U-shaped neural network (MTU-Net) is proposed and
applied to single-channel speech enhancement (SE). The proposed MTU-based SE method …
applied to single-channel speech enhancement (SE). The proposed MTU-based SE method …
Self-attentive vad: Context-aware detection of voice from noise
Recent voice activity detection (VAD) schemes have aimed at leveraging the decent neural
architectures, but few were successful with applying the attention network due to its high …
architectures, but few were successful with applying the attention network due to its high …
Framewise speech-nonspeech classification by neural networks for voice activity detection with statistical noise suppression
Y Obuchi - 2016 IEEE International Conference on Acoustics …, 2016 - ieeexplore.ieee.org
A new voice activity detection (VAD) algorithm is proposed. The proposed algorithm is the
combination of augmented statistical noise suppression (ASNS) and convolutional neural …
combination of augmented statistical noise suppression (ASNS) and convolutional neural …
Small-vocabulary speech recognition using surface electromyography
We present results of electromyographic (EMG) speech recognition on a small vocabulary of
15 English words. EMG speech recognition holds promise for mitigating the effects of high …
15 English words. EMG speech recognition holds promise for mitigating the effects of high …
The THUEE system description for the IARPA OpenASR21 challenge
This paper describes the THUEE team's speech recognition system for the IARPA Open
Automatic Speech Recognition Challenge (OpenASR21), with further experiment …
Automatic Speech Recognition Challenge (OpenASR21), with further experiment …