Amazigh Spoken Digit Recognition using a Deep Learning Approach based on MFCC

The field of speech recognition has made human-machine voice interaction more convenient. Recognizing spoken digits is particularly useful for communication that involves numbers, such as providing a registration code, cellphone number, score, or account number. This article discusses our experience with Amazigh\u27s Automatic Speech Recognition (ASR) using a deep learning- based approach. Our method involves using a convolutional neural network (CNN) with Mel-Frequency Cepstral Coefficients (MFCC) to analyze audio samples and generate spectrograms. We gathered a database of numerals from zero to nine spoken by 42 native Amazigh speakers, consisting of men and women between the ages of 20 and 40, to recognize Amazigh numerals. Our experimental results demonstrate that spoken digits in Amazigh can be recognized with an accuracy of 91.75%, 93% precision, and 92% recall. The preliminary outcomes we have achieved show great satisfaction when compared to the size of the training database. This motivates us to further enhance the system\u27s performance in order to attain a higher rate of recognition. Our findings align with those reported in the existing literature

Assessing the Performance of a Speech Recognition System Embedded in Low-Cost Devices

The main purpose of this research is to investigate how an Amazigh speech recognition system can be integrated into a low-cost minicomputer, specifically the Raspberry Pi, in order to improve the system\u27s automatic speech recognition capabilities. The study focuses on optimizing system parameters to achieve a balance between performance and limited system resources. To achieve this, the system employs a combination of Hidden Markov Models (HMMs), Gaussian Mixture Models (GMMs), and Mel Frequency Spectral Coefficients (MFCCs) with a speaker-independent approach. The system has been developed to recognize 20 Amazigh words, comprising of 10 commands and the first ten Amazigh digits. The results indicate that the recognition rate achieved on the Raspberry Pi system is 89.16% using 3 HMMs, 16 GMMs, and 39 MFCC coefficients. These findings demonstrate that it is feasible to create effective embedded Amazigh speech recognition systems using a low-cost minicomputer such as the Raspberry Pi. Furthermore, Amazigh linguistic analysis has been implemented to ensure the accuracy of the designed embedded speech system

Comparative Study of Amazigh Speech Recognition Systems Based on Different Toolkits and Approaches

The objective of this study is to evaluate and contrast the performance of different ASR approaches applied to the Amazigh language. Markovian modelling techniques, including Hidden Markov Models with Gaussian mixture distribution, Convolutional Neural Network, size of vocabulary, and lastly, the choice of decoder, whether Sphinx or HTK, by conducting a comprehensive analysis and comparison of these factors, this paper aims to provide valuable insights into the development of effective ASR systems for the Amazigh language. The findings will contribute to advancing the field of Amazigh ASR and aid in the selection of appropriate techniques and tools for future research and development efforts

On Developing an Automatic Speech Recognition System for Commonly used English Words in Indian English

Speech is one of the easiest and the fastest way to communicate. Recognition of speech by computer for various languages is a challenging task. The accuracy of Automatic speech recognition system (ASR) remains one of the key challenges, even after years of research. Accuracy varies due to speaker and language variability, vocabulary size and noise. Also, due to the design of speech recognition that is based on issues like- speech database, feature extraction techniques and performance evaluation. This paper aims to describe the development of a speaker-independent isolated automatic speech recognition system for Indian English language. The acoustic model is build using Carnegie Mellon University (CMU) Sphinx tools. The corpus used is based on Most Commonly used English words in everyday life. Speech database includes the recordings of 76 Punjabi Speakers (north-west Indian English accent). After testing, the system obtained an accuracy of 85.20 %, when trained using 128 GMMs (Gaussian Mixture Models)

Observing conflict escalation in world society

How do conflicts escalate? This is one of the major and overarching questions in conflict research. The present study makes a contribution in order to offer further answers to this question. Therefore, it has a tripartite agenda: First, it develops an empirical research strategy including a contructivist methodology for the study of conflict escalation. This strategy is embedded in a Luhmannian systems theoretical world society perspective; argues that conflicts can be understood as social systems in their own right; looks at the process of conflict escalation by analysing communication; follows a reconstructive approach informed by grounded theory and the documentary method. Second, to probe the plausibility of the approach, this study analyses two processes of conflict escalation prior to violent conflict within the framework of two systematic case studies (Maidan protests/Ukraine 2013-2014; Mali’s crisis/2010-2012). Third, on the basis of the case study insights gained and the experiences made with the empirical research strategy developed here, the present work gives some impulses and ideas on how this kind of systems theoretical research can further on be beneficial for Peace and Conflict Studies and conflict analysis in general

Observing Conflict Escalation in World Society: Ukraine's Maidan and Mali's Breakup

How do conflicts escalate? This is one of the major questions in conflict research. To offer further answers, Richard Bösch follows a tripartite agenda: First, he develops a constructivist methodology for the study of conflict escalation embedded in a Luhmannian systems theoretical world society perspective. Bösch argues that conflicts can be observed as social systems and he looks at the process of conflict escalation by analysing communication. Second, this analysis offers two case studies: the Maidan protests in Ukraine 2013-2014 and Mali's crisis 2010-2012. Third, it gives insights on how systems theoretical research can be beneficial for Peace and Conflict Studies

Migrants and Health Care: Responses by European Regions

This paper includes 11 regional reports with detailed information on health systems, rules and initiatives relating to migrants' health