Results 91 to 100 of about 7,706,916 (368)
INTERSPEECH 2023, 2023 The lack of clean speech is a practical challenge to the development of speech enhancement systems, which means that there is an inevitable mismatch between their training criterion and evaluation metric. In response to this unfavorable situation, we propose a training and inference strategy that additionally uses enhanced speech as a target by ...
Chen, Li-Wei +4 more
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Dual-Stage Low-Complexity Reconfigurable Speech Enhancement [PDF]
arXiv, 2021 This paper proposes a dual-stage, low complexity, and reconfigurable technique to enhance the speech contaminated by various types of noise sources. Driven by input data and audio contents, the proposed dual-stage speech enhancement approach performs a coarse and fine processing in the first-stage and second-stage, respectively.
arxiv
Enhancing Speech-To-Speech Translation with Multiple TTS Targets
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023 It has been known that direct speech-to-speech translation (S2ST) models usually suffer from the data scarcity issue because of the limited existing parallel materials for both source and target speech. Therefore to train a direct S2ST system, previous works usually utilize text-to-speech (TTS) systems to generate samples in the target language by ...
Shi, Jiatong +6 more
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Lightweight End-to-End Speech Enhancement Generative Adversarial Network Using Sinc Convolutions
Applied Sciences, 2021 Generative adversarial networks (GANs) have recently garnered significant attention for their use in speech enhancement tasks, in which they generally process and reconstruct speech waveforms directly.
Lujun Li +4 more
doaj +1 more source
Unsupervised Speech Enhancement with speech recognition embedding and disentanglement losses [PDF]
arXiv, 2021 Speech enhancement has recently achieved great success with various deep learning methods. However, most conventional speech enhancement systems are trained with supervised methods that impose two significant challenges. First, a majority of training datasets for speech enhancement systems are synthetic.
arxiv
Multichannel Speech Enhancement
, 2008 This chapter is an advanced tutorial about multichannel adaptive filtering for speech enhancement. Different techniques have been examined in a common foundation. Several approaches of filtering techniques were presented as the number of channels increases. The spectral equalization (power subtraction), in general, can achieve more noise reduction than
Soledad Torres-Guijarro, Lino Garcia
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Intelligent Systems with Applications, 2022 Hearing-impaired people face numerous challenges with speech perception in the presence of interfering background noise. To suppress interfering background noise, the common approach widely used is speech enhancement.
Hemangi Shinde, Vibha Vyas
doaj
IEEE Access, 2020 Human speech in real-world environments is typically degraded by the background noise. They have a negative impact on perceptual speech quality and intelligibility which causes performance degradation in various speech-related technological applications,
Nasir Saleem +3 more
doaj +1 more source
, 2017 In this letter, we derive a new super Gaussian Joint Maximum a Posteriori based single microphone speech enhancement gain function. The developed Speech Enhancement method is implemented on a smartphone, and this arrangement functions as an assistive ...
Bhat, Gautam +4 more
core +1 more source
Wiener Filter and Deep Neural Networks: A Well-Balanced Pair for Speech Enhancement
Applied Sciences, 2022 This paper proposes a Deep Learning (DL) based Wiener filter estimator for speech enhancement in the framework of the classical spectral-domain speech estimator algorithm.
Dayana Ribas +3 more
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