National Cultures and Stock Prices: Evidence from the Emerging Markets

This report in the field of behavioral finance explores the effect of national culture factors and firm specific factors on the stock prices of publicly traded firms in the 36 countries in the emerging markets. Using linear regression, we tested 13 variables (three of them were Hofstede’s indices for Individualism, Uncertainty Avoidance, and Long-term Orientation) against the stock prices. We found that in the Africa, America, and Europe regions, the cultural factors had no significant effect on stock prices. On the other hand we found that only individualistic behavior had a significant effect on stock prices in businesses in Arab and Asia. Moreover, we found that a firm’s value and investment activities had a significant impact on stock prices in Africa and Asia regions, while a firm’s size had that impact in Latin America and Arab regions

Automatic Screening of Childhood Speech Sound Disorders and Detection of Associated Pronunciation Errors

Speech disorders in children can affect their fluency and intelligibility. Delay in their diagnosis and treatment increases the risk of social impairment and learning disabilities. With the significant shortage of Speech and Language Pathologists (SLPs), there is an increasing interest in Computer-Aided Speech Therapy tools with automatic detection and diagnosis capability. However, the scarcity and unreliable annotation of disordered child speech corpora along with the high acoustic variations in the child speech data has impeded the development of reliable automatic detection and diagnosis of childhood speech sound disorders. Therefore, this thesis investigates two types of detection systems that can be achieved with minimum dependency on annotated mispronounced speech data. First, a novel approach that adopts paralinguistic features which represent the prosodic, spectral, and voice quality characteristics of the speech was proposed to perform segment- and subject-level classification of Typically Developing (TD) and Speech Sound Disordered (SSD) child speech using a binary Support Vector Machine (SVM) classifier. As paralinguistic features are both language- and content-independent, they can be extracted from an unannotated speech signal. Second, a novel Mispronunciation Detection and Diagnosis (MDD) approach was introduced to detect the pronunciation errors made due to SSDs and provide low-level diagnostic information that can be used in constructing formative feedback and a detailed diagnostic report. Unlike existing MDD methods where detection and diagnosis are performed at the phoneme level, the proposed method achieved MDD at the speech attribute level, namely the manners and places of articulations. The speech attribute features describe the involved articulators and their interactions when making a speech sound allowing a low-level description of the pronunciation error to be provided. Two novel methods to model speech attributes are further proposed in this thesis, a frame-based (phoneme-alignment) method leveraging the Multi-Task Learning (MTL) criterion and training a separate model for each attribute, and an alignment-free jointly-learnt method based on the Connectionist Temporal Classification (CTC) sequence to sequence criterion. The proposed techniques have been evaluated using standard and publicly accessible adult and child speech corpora, while the MDD method has been validated using L2 speech corpora

Speaker- and Age-Invariant Training for Child Acoustic Modeling Using Adversarial Multi-Task Learning

One of the major challenges in acoustic modelling of child speech is the rapid changes that occur in the children's articulators as they grow up, their differing growth rates and the subsequent high variability in the same age group. These high acoustic variations along with the scarcity of child speech corpora have impeded the development of a reliable speech recognition system for children. In this paper, a speaker- and age-invariant training approach based on adversarial multi-task learning is proposed. The system consists of one generator shared network that learns to generate speaker- and age-invariant features connected to three discrimination networks, for phoneme, age, and speaker. The generator network is trained to minimize the phoneme-discrimination loss and maximize the speaker- and age-discrimination losses in an adversarial multi-task learning fashion. The generator network is a Time Delay Neural Network (TDNN) architecture while the three discriminators are feed-forward networks. The system was applied to the OGI speech corpora and achieved a 13% reduction in the WER of the ASR.Comment: Submitted to ICASSP202

Phonological Level wav2vec2-based Mispronunciation Detection and Diagnosis Method

The automatic identification and analysis of pronunciation errors, known as Mispronunciation Detection and Diagnosis (MDD) plays a crucial role in Computer Aided Pronunciation Learning (CAPL) tools such as Second-Language (L2) learning or speech therapy applications. Existing MDD methods relying on analysing phonemes can only detect categorical errors of phonemes that have an adequate amount of training data to be modelled. With the unpredictable nature of the pronunciation errors of non-native or disordered speakers and the scarcity of training datasets, it is unfeasible to model all types of mispronunciations. Moreover, phoneme-level MDD approaches have a limited ability to provide detailed diagnostic information about the error made. In this paper, we propose a low-level MDD approach based on the detection of speech attribute features. Speech attribute features break down phoneme production into elementary components that are directly related to the articulatory system leading to more formative feedback to the learner. We further propose a multi-label variant of the Connectionist Temporal Classification (CTC) approach to jointly model the non-mutually exclusive speech attributes using a single model. The pre-trained wav2vec2 model was employed as a core model for the speech attribute detector. The proposed method was applied to L2 speech corpora collected from English learners from different native languages. The proposed speech attribute MDD method was further compared to the traditional phoneme-level MDD and achieved a significantly lower False Acceptance Rate (FAR), False Rejection Rate (FRR), and Diagnostic Error Rate (DER) over all speech attributes compared to the phoneme-level equivalent

Influence of deep excavation on behavior of adjacent single pile: effect of pile location

Even when located atop piles, deep excavations might result in Settlement and harm to nearby buildings. This work aims to investigate single-pile reactions to deep-braced excavation-induced soil movement in soft clay with a sand covering. The main goal of the experiment is to determine how a vertical single pile responds to produced axial force, lateral deflection, induced bending moment, and pile settlement. The pile\u27s diameter (dp) is 5 meters, and its embedded length (Lp) is 22 meters. The pile horizontally from the diaphragm wall is situated 3.75 meters (.25 He). The pile was simulated using the Embedded pile structural element. To enhance comprehension of the behavior of a single pile, a parametric analysis was conducted. to offer more information regarding the pile\u27s response. Design, procedure, and strategy A thorough three-dimensional numerical study is performed to explore pile responses during a nearby deep-braced excavation using the explicit finite element code PLAXIS 3D. Conclusions: The acquired data made it possible to fully comprehend the phenomena of soil-pile-structure interactions as well as the pile reaction. The results show that there could be significant axial forces, lateral deflections, and bending moments in the surrounding piles as a result of the deep excavation. Parametric research revealed that the position of the pile has a significant impact on the pile reactions. This work used 3D numerical modeling to fully examine the pile reaction in multi-layered soil. In this investigation, the Hardening soil model with small-strain stiffness was employed to account for the soil\u27s nonlinear small-strain behavior

Influence of deep excavation on behavior of adjacent single pile: effect of pile location

Even when located atop piles, deep excavations might result in Settlement and harm to nearby buildings. This work aims to investigate single-pile reactions to deep-braced excavation-induced soil movement in soft clay with a sand covering. The main goal of the experiment is to determine how a vertical single pile responds to produced axial force, lateral deflection, induced bending moment, and pile settlement. The pile\u27s diameter (dp) is 5 meters, and its embedded length (Lp) is 22 meters. The pile horizontally from the diaphragm wall is situated 3.75 meters (.25 He). The pile was simulated using the Embedded pile structural element. To enhance comprehension of the behavior of a single pile, a parametric analysis was conducted. to offer more information regarding the pile\u27s response. Design, procedure, and strategy A thorough three-dimensional numerical study is performed to explore pile responses during a nearby deep-braced excavation using the explicit finite element code PLAXIS 3D. Conclusions: The acquired data made it possible to fully comprehend the phenomena of soil-pile-structure interactions as well as the pile reaction. The results show that there could be significant axial forces, lateral deflections, and bending moments in the surrounding piles as a result of the deep excavation. Parametric research revealed that the position of the pile has a significant impact on the pile reactions. This work used 3D numerical modeling to fully examine the pile reaction in multi-layered soil. In this investigation, the Hardening soil model with small-strain stiffness was employed to account for the soil\u27s nonlinear small-strain behavior

Point Load Index of Rocks Exposed to High Thermal Effect

High thermal effects on Point Load Index (P.L.I) of rocks tolerate in mind an essential issue for numerous geotechnical engineering purposes. Many engineering relevancies interact with it as Geothermal power reserve extraction, Fires that occur in tunnels, Underground coal gasification (UCG), and numerous ancient monuments that were made from these rocks and exposed to different thermal impacts. This research aims to carry out Point Load Index (P.L.I) experimental studies of intact rocks as Granite, Sandstone, Marble and, Limestone rocks. In this study, the rock samples are subjected to thermal effects (from room temperature degree 25 oC to a high temperature up to 1100 oC). The results are debated and introduced in terms of rising temperature degrees with different parameters. It has been known that the Point Load Index (P.L.I) of rocks decreased with the elevated temperature, particularly outside particular temperatures.Keywords: Rock strength, Thermal Effects, Point Load Index, Different Rock