• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.1
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• pp.1-7
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• 2008

In this paper, a MSS-NOVO method that combines the HMM composition method with a noise reduction method is proposed for speech recognition in noisy environments. This combined method starts with noise reduction with modified spectral subtraction (MSS) to enhance the input noisy speech, then the noise and voice composition (NOVO) method is applied for making noise adapted models by using the noise in the non-utterance regions of the enhanced noisy speech. In order to evaluate the effectiveness of our proposed method, we compare MSS-NOVO method with other methods, i.e., SS-NOVO, MWF-NOVO. To set up the noisy speech for test, we add White noise to KLE 452 database with different SNRs range from 0dB to 15dB, at 5dB intervals. From the tests, MSS-NOVO method shows average improvement of 66.5% and 13.6% compared with the existing SS-NOVO method and MWF-NOVO method, respectively. Especially our proposed MSS-NOVO method shows a big improvement at low SNRs.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.25 no.3
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• pp.194-210
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• 2022

Human milk contains a number of nutritional and bioactive molecules including microorganisms that constitute the so-called "Human Milk Microbiota (HMM)". Recent studies have shown that not only bacterial but also viral, fungal, and archaeal components are present in the HMM. Previous research has established, a "core" microbiome, consisting of Firmicutes (i.e., Streptococcus, Staphylococcus), Proteobacteria (i.e., Serratia, Pseudomonas, Ralstonia, Sphingomonas, Bradyrhizobium), and Actinobacteria (i.e., Propionibacterium, Corynebacterium). This review aims to summarize the main characteristics of HMM and the role it plays in shaping a child's health. We reviewed the most recent literature on the topic (2019-2021), using the PubMed database. The main sources of HMM origin were identified as the retrograde flow and the entero-mammary pathway. Several factors can influence its composition, such as maternal body mass index and diet, use of antibiotics, time and type of delivery, and mode of breastfeeding. The COVID-19 pandemic, by altering the mother-infant dyad and modifying many of our previous habits, has emerged as a new risk factor for the modification of HMM. HMM is an important contributor to gastrointestinal colonization in children and therefore, it is fundamental to avoid any form of perturbation in the HMM that can alter the microbial equilibrium, especially in the first 100 days of life. Microbial dysbiosis can be a trigger point for the development of necrotizing enterocolitis, especially in preterm infants, and for onset of chronic diseases, such as asthma and obesity, later in life.

• The Journal of the Acoustical Society of Korea
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• v.25 no.4
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• pp.159-163
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• 2006

In this paper a data-driven method to improve the performance of the Jacobian adaptation (JA) for the noisy speech recognition is proposed. In stead of constructing the reference HMM by using the model composition method like the parallel model combination (PMC), we propose to train the reference HMM directly with the noisy speech. This was motivated from the idea that the directly trained reference HMM will model the acoustical variations due to the noise better than the composite HMM. For the estimation of the Jacobian matrices, the Baum-Welch algorithm is employed during the training. The recognition experiments have been done to show the improved performance of the proposed method over the Jacobian adaptation as well as other model compensation methods.