DeLiang Wang,Jitong Chen
DeLiang Wang
Speech separation is the task of separating target speech from background interference. Traditionally, speech separation is studied as a signal processing problem. A more recent approach formulates speech separation as a supervised learning...
Yan Zhao,Zhong-Qiu Wang,DeLiang Wang
Yan Zhao
In real-world situations, speech reaching our ears is commonly corrupted by both room reverberation and background noise. These distortions are detrimental to speech intelligibility and quality, and also pose a serious problem to many speec...
Dongmei Wang,Chengzhu Yu,John H L Hansen
Dongmei Wang
Pitch estimation in diverse naturalistic audio streams remains a challenge for speech processing and spoken language technology. In this study, we investigate the use of robust harmonic features for classification-based pitch estimation. Th...
Acoustic Denoising using Dictionary Learning with Spectral and Temporal Regularization [0.03%]
基于频域和时域正则化的字典学习降噪算法
Colin Vaz,Vikram Ramanarayanan,Shrikanth Narayanan
Colin Vaz
We present a method for speech enhancement of data collected in extremely noisy environments, such as those obtained during magnetic resonance imaging (MRI) scans. We propose an algorithm based on dictionary learning to perform this enhance...
Speaker-Independent Silent Speech Recognition from Flesh-Point Articulatory Movements Using an LSTM Neural Network [0.03%]
基于LSTM神经网络的独立说话人无声言语识别方法
Myungjong Kim,Beiming Cao,Ted Mau et al.
Myungjong Kim et al.
Silent speech recognition (SSR) converts non-audio information such as articulatory movements into text. SSR has the potential to enable persons with laryngectomy to communicate through natural spoken expression. Current SSR systems have la...
Time-Frequency Masking in the Complex Domain for Speech Dereverberation and Denoising [0.03%]
复数域时频掩模在语音去混响及降噪中的应用
Donald S Williamson,DeLiang Wang
Donald S Williamson
In real-world situations, speech is masked by both background noise and reverberation, which negatively affect perceptual quality and intelligibility. In this paper, we address monaural speech separation in reverberant and noisy environment...
A Framework for Speech Activity Detection Using Adaptive Auditory Receptive Fields [0.03%]
基于自适应听觉感受野的语音活动检测框架
Michael A Carlin,Mounya Elhilali
Michael A Carlin
One of the hallmarks of sound processing in the brain is the ability of the nervous system to adapt to changing behavioral demands and surrounding soundscapes. It can dynamically shift sensory and cognitive resources to focus on relevant so...
Silent Speech Recognition as an Alternative Communication Device for Persons with Laryngectomy [0.03%]
用于喉切除患者的隐蔽式言语识别型交流辅助装置研究
Geoffrey S Meltzner,James T Heaton,Yunbin Deng et al.
Geoffrey S Meltzner et al.
Each year thousands of individuals require surgical removal of their larynx (voice box) due to trauma or disease, and thereby require an alternative voice source or assistive device to verbally communicate. Although natural voice is lost af...
Deep Learning Based Binaural Speech Separation in Reverberant Environments [0.03%]
基于深度学习的双声道语音分离在混响环境中的应用
Xueliang Zhang,DeLiang Wang
Xueliang Zhang
Speech signal is usually degraded by room reverberation and additive noises in real environments. This paper focuses on separating target speech signal in reverberant conditions from binaural inputs. Binaural separation is formulated as a s...
Feedback-Driven Sensory Mapping Adaptation for Robust Speech Activity Detection [0.03%]
基于反馈的感官映射自适应鲁棒语音活动检测方法
Ashwin Bellur,Mounya Elhilali
Ashwin Bellur
Parsing natural acoustic scenes using computational methodologies poses many challenges. Given the rich and complex nature of the acoustic environment, data mismatch between train and test conditions is a major hurdle in data-driven audio p...