Results 51 to 60 of about 7,706,916 (368)
EURASIP Journal on Advances in Signal Processing, 2017 Acoustic echo cancellation (AEC) is a key speech enhancement technology in speech communication and voice-enabled devices. AEC systems employ adaptive filters to estimate the acoustic echo paths between the loudspeakers and the microphone(s).
Naveen Kumar Desiraju +2 more
doaj +1 more source
Dual-Branch Attention-In-Attention Transformer for Single-Channel Speech Enhancement [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2021 Curriculum learning begins to thrive in the speech enhancement area, which decouples the original spectrum estimation task into multiple easier sub-tasks to achieve better performance.
Guochen Yu +5 more
semanticscholar +1 more source
Vocal Pitch Discrimination in Children with and without Vocal Fold Nodules
Applied Sciences, 2019 Vocal pitch discrimination abilities were compared in sixteen children with vocal fold nodules (CwVN) and sixteen matched controls with typical voices (CwTV).
Elizabeth S. Heller Murray +4 more
doaj +1 more source
IEEE/ACM Transactions on Audio Speech and Language Processing, 2020 Phase is important for perceptual quality of speech. However, it seems intractable to directly estimate phase spectra through supervised learning due to their lack of spectrotemporal structure in it. Complex spectral mapping aims to estimate the real and
Ke Tan, Deliang Wang
semanticscholar +1 more source
International Journal of Interactive Multimedia and Artificial Intelligence, 2020 Many forms of human communication exist; for instance, text and nonverbal based. Speech is, however, the most powerful and dexterous form for the humans.
Elena Verdú +2 more
doaj +1 more source
Speech Perception Improvement Algorithm Based on a Dual-Path Long Short-Term Memory Network
Bioengineering, 2023 Current deep learning-based speech enhancement methods focus on enhancing the time–frequency representation of the signal. However, conventional methods can lead to speech damage due to resolution mismatch problems that emphasize only specific ...
Hyeong Il Koh +2 more
doaj +1 more source
Fullsubnet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020 This paper proposes a full-band and sub-band fusion model, named as FullSubNet, for single-channel real-time speech enhancement. Full-band and sub-band refer to the models that input full-band and sub-band noisy spectral feature, output full-band and sub-
Xiang Hao +3 more
semanticscholar +1 more source
Deepfilternet: A Low Complexity Speech Enhancement Framework for Full-Band Audio Based On Deep Filtering [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2021 Complex-valued processing has brought deep learning-based speech enhancement and signal extraction to a new level. Typically, the process is based on a time-frequency (TF) mask which is applied to a noisy spectrogram, while complex masks (CM) are usually
Hendrik Schröter +3 more
semanticscholar +1 more source
Scaling Speech Enhancement in Unseen Environments with Noise Embeddings [PDF]
, 2018 We address the problem of speech enhancement generalisation to unseen environments by performing two manipulations. First, we embed an additional recording from the environment alone, and use this embedding to alter activations in the main enhancement ...
Han, Jing, Keren, Gil, Schuller, Björn
core +2 more sources
TSTNN: Two-Stage Transformer Based Neural Network for Speech Enhancement in the Time Domain [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2021 In this paper, we propose a transformer-based architecture, called two-stage transformer neural network (TSTNN) for end-to-end speech denoising in the time domain.
Kai Wang, Bengbeng He, Weiping Zhu
semanticscholar +1 more source