Comparison of Mel Frequency Cepstral Coefficient (MFCC) Feature Extraction, With and Without Framing Feature Selection, to Test the Shahada Recitation

Voice research for feature extraction using MFCC. Introduction with feature extraction as the first step to get features. Features need to be done further through feature selection. The feature selection in this research used the Dominant Weight feature for the Shahada voice, which produced frames and cepstral coefficients as the feature extraction. The cepstral coefficient was used from 0 to 23 or 24 cepstral coefficients. At the same time, the taken frame consisted of 0 to 10 frames or eleven frames. Voting as many as 300 samples of recorded voices were tested on 200 voices of both male and female voice recordings. The frequency used was 44.100 kHz 16-bit stereo. This research aimed to gain accuracy by selecting the right features on the frame using MFCC feature extraction and matching accuracy with frame feature selection using the Dominant Weight Normalization (NBD). The accuracy results obtained that the MFCC method with the selection of the 9th frame had a higher accuracy rate of 86% compared to other frames. The MFCC without feature selection had an average of 60%. The conclusion was that selecting the right features in the 9th frame impacted the accuracy of the voice of shahada recitation.

Classification of Javanese Script Hanacara Voice Using Mel Frequency Cepstral Coefficient MFCC and Selection of Dominant Weight Features

This study investigates the sound of Hanacaraka in Javanese to select the best frame feature in checking the reading sound. Selection of the right frame feature is needed in speech recognition because certain frames have accuracy at their dominant weight, so it is necessary to match frames with the best accuracy. Common and widely used feature extraction models include the Mel Frequency Cepstral Coefficient (MFCC). The MFCC method has an accuracy of 50% to 60%. This research uses MFCC and the selection of Dominant Weight features for the Javanese language script sound Hanacaraka which produces a frame and cepstral coefficient as feature extraction. The use of the cepstral coefficient ranges from 0 to 23 or as many as 24 cepstral coefficients. In comparison, the captured frame consists of 0 to 10 frames or consists of eleven frames. A sound sampling of 300 recorded voice sampling was tested on 300 voice recordings of both male and female voice recordings. The frequency used is 44,100 kHz 16-bit stereo. The accuracy results show that the MFCC method with the ninth frame selection has a higher accuracy rate of 86% than other frames.

Good Morning to Good Night Greeting Classification Using Mel Frequency Cepstral Coefficient (MFCC) Feature Extraction and Frame Feature Selection

Purpose:Select the right features on the frame for good accuracyDesign/methodology/approach:Extraction of Mel Frequency Cepstral Coefficient (MFCC) Features and Selection of Dominant Weight Normalized (DWN) FeaturesFindings/result:The accuracy results show that the MFCC method with the 9th frame selection has a higher accuracy rate of 85% compared to other frames.Originality/value/state of the art:Selection of the appropriate features on the frame.

The Effects of a 9-Week Hip Focused Weight Training Program on Hip And Knee Kinematics and Kinetics in Experienced Female Dancers

Increased involvement of the hip musculature during some movements is associated with enhanced performance and reduced injury risk. However, the impact of hip dominant weight training methods on movement strategy has seen limited attention within the literature. The aim of this study was to evaluate if a 9-week hip dominant weight training intervention promotes a more hip dominant movement strategy leading to an improvement in countermovement jump performance. Twenty-two experienced female dancers were recruited and separated into an intervention (age 24.4 ± 6.3 years, body height 165.5 ± 5.8 cm, body mass 65.9 ± 5.6 kg) and a control (age 22.9 ± 5.6 years, body height 163.3 ± 5.4 cm, body mass 57.4 ± 6.8 kg) group. The intervention group participated in a 9-week hip dominant training intervention, which consisted of a wide stance back squat, Romanian deadlift, hip thrusters, and a bent over row. Hip and knee kinematics and kinetics, and countermovement jump performance were assessed pre and post training. Significant interaction effects were found for peak hip joint moment (p = 0.030, η2 = 0.214) and countermovement jump performance (p = 0.003, η2 = 0.356), indicating an increase in peak hip joint moment and countermovement jump performance for the intervention group. Specifically, the intervention group showed a mean increase in jump height of 11.5%. The data show that the use of a hip dominant weight training strategy can improve hip contribution in the propulsion phase of the countermovement jump. Strength and conditioning specialists should incorporate hip dominant weight training exercises to increase hip strength and improve performance.

A Modified Lung Ultrasound Score for Assessing Oxygenation Status and Predicting the Need for Invasive Ventilation in Preterm Neonates with RDS

PurposeWe propose a modified lung ultrasound score (LUS) in neonates with respiratory distress syndrome (RDS), which includes posterior instead of lateral lung fields, and a 5-grade rating scale instead of a 4-grade rating scale. The LUS was evaluated for validity, interrater agreement and prognostic power in relation to the need for respiratory support on day of life (DOL) 3. The hypothesis of the dominant weight of posterior scans in the LUS was also verified.Materials and methodsA total of 647 serial lung scans were performed in 70 preterm infants <32 weeks gestation and birth weight <1500 g. Assessments were performed within 24 hours of birth (LUS0) and on days 2, 3, 5, 7, 10, 14, 21 and 28. LUS was correlated to oxygen saturation over fraction of inspired oxygen (SpO2/FiO2) and mode of respiratory support. Probabilities of the need for respiratory support on DOL 3 were assessed with ordinal logistic regression.ResultsThe LUS correlated significantly with SpO2/FiO2 (Spearman rho = -0.635; p<0.0001) and had excellent interrater agreement (Cronbach’s alpha = 0.99). Posterior fields had dominant weight over the anterior fields (ls mean [confidence level]) 4.0 [3.8–4.1] vs 2.2 [2.0–2.4]; p<0.0001. Significant predictors of ventilation requirements on DOL 3 were LUS0 (p<0.016) and birth weight (BW) (p<0.0001); invasive ventilation was the most likely option with LUS0 ≥7 (BW 900 g), ≥10 (BW 1050 g) and ≥15 (BW 1280 g).ConclusionPostbirth LUS predicts the need for mechanical ventilation on DOL 3. Posterior fields play a dominant role in sonographic assessment of lungs in neonatal RDS.

Matrix-Ball Construction of affine Robinson-Schensted correspondence

International audience In his study of Kazhdan-Lusztig cells in affine type A, Shi has introduced an affine analog of Robinson- Schensted correspondence. We generalize the Matrix-Ball Construction of Viennot and Fulton to give a more combi- natorial realization of Shi's algorithm. As a biproduct, we also give a way to realize the affine correspondence via the usual Robinson-Schensted bumping algorithm. Next, inspired by Honeywill, we extend the algorithm to a bijection between extended affine symmetric group and triples (P, Q, ρ) where P and Q are tabloids and ρ is a dominant weight. The weights ρ get a natural interpretation in terms of the Affine Matrix-Ball Construction. Finally, we prove that fibers of the inverse map possess a Weyl group symmetry, explaining the dominance condition on weights.

Maximal Weight Composition Factors for Weyl Modules

Fix an irreducible (finite) root system R and a choice of positive roots. For any algebraically closed field k consider the almost simple, simply connected algebraic group Gk over k with root system k. One associates with any dominant weight λ for R two Gk-modules with highest weight λ, the Weyl module V( λ)k and its simple quotient L(µ)k . Let λ and μ be dominant weights with μ < j such that μ is maximal with this property. Garibaldi, Guralnick, and Nakano have asked under which condition there exists k such that L(μ)k is a composition factor of V(j)k , and they exhibit an example in type E8 where this is not the case. The purpose of this paper is to to show that their example is the only one. It contains two proofs for this fact: one that uses a classiffication of the possible pairs (λ, μ), and another that relies only on the classiûcation of root systems.