Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attention-based convolutional neural network (CNN) model. To address age ambiguity, we evaluate the effects of different loss functions such as focal loss and Kullback-Leibler (KL) divergence loss. Additionally, we evaluate the accuracy of the estimation at different durations of speech. Experimental results from the Common Voice dataset underscore the efficacy of our approach, showcasing an accuracy of 87% for male speakers, 91% for female speakers and 89% overall accuracy, and an accuracy of 99.1% for gender prediction.
Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.
Investigating the strength and the relationship between the Self-organized learning strategies and self-competence among talented students was the aim of this study. To do this, the researcher employed the correlation descriptive approach, whereby a sample of (120) male and female student were selected from various Iraqi cities for the academic year 2015-2016. the researcher setup two scales based on the previous studies: one to measure the Self-organized learning strategies which consist of (47) item and the other to measure the self-competence that composed of (50) item. Both of these scales were applied on the targeted sample to collect the required data
The architecture of the richly decorated mosques demonstrated that the Islamic culture is one of the most significant and greatest civilizations in the history of humanity. The plant decorative units are one of the key areas in which the Muslim artist excelled. As a result, he created various plant forms that he took from nature, which led him to invent the arabesque art consisting of plant motifs with curved and rounded lines or wrapped between them. These shapes with curved borders include leaves, twigs, and flowers. Buildings and artefacts from the nineteenth century AD have this shape. they achieved their objectives during the twelfth and thirteenth centuries. There was another kind of vegetable decorative unit, made up of stems and
... Show Morein this paper we adopted ways for detecting edges locally classical prewitt operators and modification it are adopted to perform the edge detection and comparing then with sobel opreators the study shows that using a prewitt opreators
Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E
... Show MoreThe main objective of this work was to adopt an environmentally friendly technology with enhanced results. The technology of magnetic water (MW) treatment system can be used in concrete mixture production instead of potable water (PW) to improve both workability and strength. Two types of concrete were adopted: normal concreter production with two grades 25 and 35 MPa and the self-compacted concrete (SCC) with 35 MPa grade. The concrete mixes containing MW instead of PW results showed that, for 25 MPa grade, an improvement in a compressive strength of 15.1, 14.8, and 10.2% was achieved for 7, 28, and 90 days, respectively. For 35 MPa grade, an improvement of 13.6, 11.5, and
The main objective of this work was to adopt an environmentally friendly technology with enhanced results. The technology of magnetic water (MW) treatment system can be used in concrete mixture production instead of potable water (PW) to improve both workability and strength. Two types of concrete were adopted: normal concreter production with two grades 25 and 35 MPa and the self-compacted concrete (SCC) with 35 MPa grade. The concrete mixes containing MW instead of PW results showed that, for 25 MPa grade, an improvement in a compressive strength of 15.1, 14.8, and 10.2% was achieved for 7, 28, and 90 days, respectively. For 35 MPa grade, an improvement of 13.6, 11.5, and
This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.
The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20
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