This paper presents a deep neural network(DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the ps...This paper presents a deep neural network(DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the psychoacoustic model is adopted to calculate the masking threshold from the estimated clean speech spectrum. The gain for noise suppression is obtained based on soft audible noise masking by comparing the estimated wind noise spectrum with the masking threshold. To deal with the abruptly time-varying noisy signals, two separate DNN models are utilized to estimate the spectra of clean speech and wind noise components. Experimental results on the subjective and objective quality tests show that the proposed algorithm achieves the better performance compared with the conventional DNN-based wind noise reduction method.展开更多
Introduction: Expiratory upper airway obstruction during bag-mask ventilation is not well characterized. Methods: An audit was done to assess expiratory obstruction in 90 adult surgical patients undergoing bag-mask ve...Introduction: Expiratory upper airway obstruction during bag-mask ventilation is not well characterized. Methods: An audit was done to assess expiratory obstruction in 90 adult surgical patients undergoing bag-mask ventilation during the induction of general anaesthesia. Results: Clinicians experienced difficulty delivering gas to the lungs when the head was neutral in 52 of 90 patients (58%;inspiratory obstruction) but this problem was corrected by head tilt and chin lift in all but 2 patients. Clinicians experienced difficulty recovering gas from the lungs when the mouth was held closed under the mask in 30 of the remaining 88 patients (34%;expiratory obstruction). This problem persisted despite head tilt and chin lift in all but one patient but was uniformly corrected by opening the mouth. Inspection of the soft palate revealed that it was lying on the posterior pharyngeal wall in 27 of 30 patients with expiratory obstruction and that the retropalatal space was patent in 55 of 58 patients without expiratory obstruction (χ2, P < 0.001). The clinical predictors of expiratory upper airway obstruction included advanced age, large tongue, and large uvula. Conclusion: Expiratory airway obstruction should be suspected in all cases of difficult mask ventilation that cannot be corrected by head tilt and chin lift. Simply allowing the mouth to open between positive pressure breaths will permit gas to exit the lungs.展开更多
Many speech enhancement algorithms that deal with noise reduction are based on a binary masking decision(termed as the hard decision), which may cause some regions of the synthesized speech to be discarded. In view of...Many speech enhancement algorithms that deal with noise reduction are based on a binary masking decision(termed as the hard decision), which may cause some regions of the synthesized speech to be discarded. In view of the problem, a soft decision is often used as an optimal technique for speech restoration. In this paper, considering a new fashion of speech and noise models, we present two model-based soft decision techniques. One technique estimates a ratio mask generated by the exact Bayesian estimators of speech and noise. For the second technique, we consider one issue that an optimum local criterion(LC) for a certain SNR may not be appropriate for other SNRs. So we estimate a probabilistic mask with a variable LC. Experimental results show that the proposed method achieves a better performance than reference methods in speech quality.展开更多
基金partially supported by the National Natural Science Foundation of China (Nos.11590772, 11590770)the Pre-research Project for Equipment of General Information System (No.JZX2017-0994/Y306)
文摘This paper presents a deep neural network(DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the psychoacoustic model is adopted to calculate the masking threshold from the estimated clean speech spectrum. The gain for noise suppression is obtained based on soft audible noise masking by comparing the estimated wind noise spectrum with the masking threshold. To deal with the abruptly time-varying noisy signals, two separate DNN models are utilized to estimate the spectra of clean speech and wind noise components. Experimental results on the subjective and objective quality tests show that the proposed algorithm achieves the better performance compared with the conventional DNN-based wind noise reduction method.
文摘Introduction: Expiratory upper airway obstruction during bag-mask ventilation is not well characterized. Methods: An audit was done to assess expiratory obstruction in 90 adult surgical patients undergoing bag-mask ventilation during the induction of general anaesthesia. Results: Clinicians experienced difficulty delivering gas to the lungs when the head was neutral in 52 of 90 patients (58%;inspiratory obstruction) but this problem was corrected by head tilt and chin lift in all but 2 patients. Clinicians experienced difficulty recovering gas from the lungs when the mouth was held closed under the mask in 30 of the remaining 88 patients (34%;expiratory obstruction). This problem persisted despite head tilt and chin lift in all but one patient but was uniformly corrected by opening the mouth. Inspection of the soft palate revealed that it was lying on the posterior pharyngeal wall in 27 of 30 patients with expiratory obstruction and that the retropalatal space was patent in 55 of 58 patients without expiratory obstruction (χ2, P < 0.001). The clinical predictors of expiratory upper airway obstruction included advanced age, large tongue, and large uvula. Conclusion: Expiratory airway obstruction should be suspected in all cases of difficult mask ventilation that cannot be corrected by head tilt and chin lift. Simply allowing the mouth to open between positive pressure breaths will permit gas to exit the lungs.
基金supported by the National Natural Science Foundation of China (Grant No.61471014,61231015)
文摘Many speech enhancement algorithms that deal with noise reduction are based on a binary masking decision(termed as the hard decision), which may cause some regions of the synthesized speech to be discarded. In view of the problem, a soft decision is often used as an optimal technique for speech restoration. In this paper, considering a new fashion of speech and noise models, we present two model-based soft decision techniques. One technique estimates a ratio mask generated by the exact Bayesian estimators of speech and noise. For the second technique, we consider one issue that an optimum local criterion(LC) for a certain SNR may not be appropriate for other SNRs. So we estimate a probabilistic mask with a variable LC. Experimental results show that the proposed method achieves a better performance than reference methods in speech quality.
