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In this paper, the multidimensional phonological feature structure of Arabic is investigated. Our goal is to assess the performance of statistical and connectionist approaches in performing the complex mappings between distinctive phonetic features (DPF) and associated acoustic cues. The present study explores the mapping between 29 phonological voicing, place, and manner features and Mel-frequency...
The Throat Microphone (TM) is a non-acoustic device, relying on the vibrations of vocal folds rather than the audible sound produced. Correctly capturing vocal fold vibrations is difficult due to poor signal representation capabilities. The system recognizes the TM vibrations and produces the corresponding speech sound. This is done by extracting features from the spectrum of the TM vibrations and...
Feature selection is a crucial step in the development of a system for identifying emotions in speech. How to select high correlation features is an open question. This paper focuses on feature selection method which aims to extract the most effective acoustic features to improve the performance of emotion recognition. Emotional feature selection of speaker-independent speech based on Random Forest...
The design of speaker diarisation and recognition systems is a mature research area and their deployment in the real world has gained momentum. There are still a number of parameters of these systems that have to be tuned and optimised for the application scenario at hand. An online call recording diarisation system is designed with integrated speaker identification of the call-centre operators. The...
The paper presents the emotions recognition for positive and negative emotions for Romanian language. The main purpose of this study is to highlight how emotions are recognized if it is not wanted to identify with precision the expressed emotion, but the emotion in general: positive, negative or neutral. This can be useful for a human-machine interface. The positive emotions were recognized with an...
This paper proposes a competent system that is not only text independent in identifying gender of a speaker but can also work efficiently in noisy environmental conditions in real time. The noisy environmental conditions are the places where noise signals are generated at different SNRs (Signal to Noise Ratios) such as train station, restaurant, exhibition hall, airport, and so on. The algorithms...
This paper examines the development of a speaker identification system (SIS) for future aeronautical communication systems. SIS promises to improve flight safety by reducing the incidence of call-sign confusion events. However, the practical development of such a system faces many challenges, especially related to the signal corruption by the channel noise. Due to the dynamic motion of aircraft, the...
Vocal impairments are one of the earliest disrupted modalities in Parkinson's disease (PD). Most of the studies whose aim was to detect Parkinson's disease through acoustic analysis use global parameters. In the meantime, in speaker and speech recognition, analyses are carried out by short-term parameters, and more precisely by Mel-Frequency Cepstral Coefficients (MFCC), combined with Gaussian Mixture...
The act of learning and teaching of the Qur'an is the most important science for Muslim. The teacher and learner in this area they should have the provisions of tajweed rules when reading the Qur'an. There are numerous efforts made by previous systems on the development of feasible guiding techniques to the act of Tajweed. However, liking the major control variables of the practices of Tajweed in...
Albeit recent progress in speaker verification engendered powerful models, malicious attacks in the form of spoofed speech, are generally not coped with. In previous attempts, deep neural networks were used to extract high dimensional features which were later classified using an independent classifier. Even though the results of this approach are promising, this architecture's disadvantage is it's...
In proposed speech to text conversion, a Support Vector Machines (SVM) based Turkish speech to text converter system has been developed. In the recognition system, Mel Frequency Cepstral Coefficients (MFCC) has been applied to extract features of Turkish speech and SVM based classifier has been used to classify the phonemes. The morphological structure of Turkish, a language based on phonemes, has...
in this study the Nave Bayes Network NBN classifier is used for automatic vocal folds pathologies detection and classification. The proposed method is based on the acoustic parameters extraction such as Mel Frequency Cepstral Coefficient (MFCC), jitter, shimmer and fundamental frequency which are used as inputs to NBN classifier to discriminate between three different groups: speakers with normal...
Speaker identification is a field of which usage grows faster in security systems and forensic sciences. Depending on the tasks, online or offline applications are presented. It is an important problem that how much they are accurate, how much they are fast or how hard is its computation. In this study, the accuracy and the speed of the classifiers that can be used on speaker identification and the...
This paper presents a study on how the performance of Phonetic engine(PE) varies with different set of spectral features selected for it. An exclusive study is carried out with a PE developed in the Manipuri language. Here, we built the PE using phonetic transcriptions and modeling of each phonetic unit by Hidden Markov Model (HMM). The symbols of International Phonetic Alphabet (IPA) (revised in...
This paper presents the implementation of a practical voice recognition system using MATLAB (R2014b) to secure a given user's system so that only the user may access it. Voice recognition systems have two phases, training and testing. During the training phase, the characteristic features of the speaker are extracted from the speech signal and stored in a database. In the testing phase, the stored...
In recent years the emotion recognition from speech is area of more interest in human computer interaction. There are many different researchers which worked on emotion recognition from speech with different systems. This paper attempts emotion recognition from speech which is language independent. The emotional speech samples database is used for feature extraction. For feature extraction MFCC and...
Echo cancellation has always in the preprocessing steps before the signals are converted to feature vectors and pattern classification. This is always the correct flow of speech identification. Therefore, in order to get the best cleaned signal, the usage of adaptive echo cancellation removed the echo and also the noise which deteriorates the signals and final results during classification process...
This paper aims to compare the Linear Predictive Cepstral Coefficients (LPCC) method, the Mel-frequency Cepstral Coefficient (MFCC) method, their concatenation (LPCC-MFCC), and a new proposed feature fusion approach based on method involving this concatenation with the respective averages normalization; Linear predictive and Mel-frequency Cepstral Coefficients (LMACC) through applying a multi-layer...
Home automation provides convenient, comfortable, energy saving, safety and security to people. Nowadays mostly home automation systems are based on English speech recognition. In northern Pakistan where majority of the people speaks Pashto and the literacy rate is very low, due to which most of the people deprived from the use of home automation. The aim of this research is to provide a friendly...
Visual acuity tests are performed by doctors to assess a patient's visual acuity. Health practitioners carry out this test manually on daily basis. This proposed technique aims at the ease of accurately testing vision anywhere instead of planning a visit to a practitioner. In this interactive method, a user utters isolated words as a guess input to the system from a table of selected words. The system...
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