Search results for: SPEECH EMOTION RECOGNITION - Bridge of Knowledge

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Search results for: SPEECH EMOTION RECOGNITION

Search results for: SPEECH EMOTION RECOGNITION

  • Compulsive sexual behavior and dysregulation of emotion

    Publication

    - Sexual Medicine Reviews - Year 2020

    Introduction Dysregulation of emotion (DE) is commonly seen in individuals suffering from compulsive sexual behavior (CSB), as well as represents a crucial element of its common comorbidities like mood, anxiety, and substance use disorders. Aim To investigate the links between CSB and DE. Methods A review of pertinent literature on CSB and DE was performed using EBSCO, PubMed, and Google Scholar databases. Main Outcome Measure...

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  • Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech

    Publication
    • D. Korzekwa
    • R. Barra-Chicote
    • B. Kostek
    • T. Drugman
    • M. Łajszczak

    - Year 2019

    We present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...

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  • Comparison of various speech time-scale modificartion methods

    The objective of this work is to investigate the influence of the different time-scale modification (TSM) methods on the quality of the speech stretched up using the designed non-uniform real-time speech time-scale modification algorithm (NU-RTSM). The algorithm provides a combination of the typical TSM algorithm with the vowels, consonants, stutter, transients and silence detectors. Based on the information about the content and...

  • Speech codec enhancements utilizing time compression and perceptual coding

    Publication

    A method for encoding wideband speech signal employing standardized narrowband speech codecs is presented as well as experimental results concerning detection of tonal spectral components. The speech signal sampled with a higher sampling rate than it is suitable for narrowband coding algorithm is compressed in order to decrease the amount of samples. Next, the time-compressed representation of a signal is encoded using a narrowband...

  • Tensor Decomposition for Imagined Speech Discrimination in EEG

    Publication

    - LECTURE NOTES IN COMPUTER SCIENCE - Year 2018

    Most of the researches in Electroencephalogram(EEG)-based Brain-Computer Interfaces (BCI) are focused on the use of motor imagery. As an attempt to improve the control of these interfaces, the use of language instead of movement has been recently explored, in the form of imagined speech. This work aims for the discrimination of imagined words in electroencephalogram signals. For this purpose, the analysis of multiple variables...

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  • Methods of Improving Speech Intelligibility for Listeners with Hearing Resolution Deficit

    Methods developed for real-time time scale modification (TSM) of speech signal are presented. They are based onthe non-uniform, speech rate depended SOLA algorithm (Synchronous Overlap and Add). Influence of theproposed method on the intelligibility of speech was investigated for two separate groups of listeners, i.e. hearingimpaired children and elderly listeners. It was shown that for the speech with average rate equal to or...

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  • Recognition and sensing of anions

    Publication

    Molecular ion recognition is one of the most intensively studied areas of supramolecular technology. The reason for this is the essential role that ions play in many biological as well as industrial processes. On the other hand, however, it has been proved that ions can have a negative impact on human health and the environment. For these reasons, it is extremly important to develop rapid and simple methods allowing the determination...

  • Investigating Noise Interference on Speech Towards Applying the Lombard Effect Automatically

    Publication

    - Year 2022

    The aim of this study is two-fold. First, we perform a series of experiments to examine the interference of different noises on speech processing. For that purpose, we concentrate on the Lombard effect, an involuntary tendency to raise speech level in the presence of background noise. Then, we apply this knowledge to detecting speech with the Lombard effect. This is for preparing a dataset for training a machine learning-based...

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  • Bimodal deep learning model for subjectively enhanced emotion classification in films

    Publication

    - INFORMATION SCIENCES - Year 2024

    This research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....

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  • System Supporting Speech Perception in Special Educational Needs Schoolchildren

    Publication

    - Year 2012

    The system supporting speech perception during the classes is presented in the paper. The system is a combination of portable device, which enables real-time speech stretching, with the workstation designed in order to perform hearing tests. System was designed to help children suffering from Central Auditory Processing Disorders.

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  • Computational Approaches to Modeling Artificial Emotion – An Overview of the Proposed Solutions

    Cybernetic approach to modeling artificial emotion through the use of different theories of psychology is considered in this paper, presenting a review of twelve proposed solutions: ActAffAct, FLAME, EMA, ParleE, FearNot!, FAtiMA, WASABI, Cathexis, KARO, MAMID, FCM, and xEmotion. The main motivation for this study is founded on the hypothesis that emotions can play a definite utility role of scheduling variables in the construction...

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  • High quality speech codec employing sines+noise+transients model

    A method of high quality wideband speech signal representation employing sines+transients+noise model is presented. The need for a wideband speech coding approach as well as various methods for analysis and synthesis of sines, residual and transient states of speech signal is discussed. The perceptual criterion is applied in the proposed approach during encoding of sines amplitudes in order to reduce bandwidth requirements and...

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  • Silence/noise detection for speech and music signals

    Publication

    - Year 2008

    This paper introduces a novel off-line algorithm for silence/noise detection in noisy signals. The main concept of the proposed algorithm is to provide noise patterns for further signals processing i.e. noise reduction for speech enhancement. The algorithm is based on frequency domain characteristics of signals. The examples of different types of noisy signals are presented.

  • Virtual keyboard controlled by eye gaze employing speech synthesis

    Publication

    - Year 2010

    The article presents the speech synthesis integrated into the eye gaze tracking system. This approach can significantly improve the quality of life of physically disabled people who are unable to communicate. The virtual keyboard (QWERTY) is an interface which allows for entering the text for the speech synthesizer. First, this article describes a methodology of determining the fixation point on a computer screen. Then it presents...

  • Virtual Keyboard controlled by eye gaze employing speech synthesis

    The article presents the speech synthesis integrated into the eye gaze tracking system. This approach can significantly improve the quality of life of physically disabled people who are unable to communicate. The virtual keyboard (QWERTY) is an interface which allows for entering the text for the speech synthesizer. First, this article describes a methodology of determining the fixation point on a computer screen. Then it presents...

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  • Analysis of Lombard speech using parameterization and the objective quality indicators in noise conditions

    Publication

    - Year 2018

    The aim of the work is to analyze Lombard speech effect in recordings and then modify the speech signal in order to obtain an increase in the improvement of objective speech quality indicators after mixing the useful signal with noise or with an interfering signal. The modifications made to the signal are based on the characteristics of the Lombard speech, and in particular on the effect of increasing the fundamental frequency...

  • Corrupted speech intelligibility improvement using adaptive filter based algorithm

    Publication

    A technique for improving the quality of speech signals recorded in strong noise is presented. The proposed algorithmemploying adaptive filtration is described and additional possibilities of speech intelligibility improvement arediscussed. Results of the tests are presented.

  • Distortion of speech signals in the listening area: its mechanism and measurements

    Publication

    - Year 2014

    The paper deals with a problem of the influence of the number and distribution of loudspeakers in speech reinforcement systems on the quality of publicly addressed voice messages, namely on speech intelligibility in the listening area. Linear superposition of time-shifted broadband waves of a same form and slightly different magnitudes that reach a listener from numerous coherent sources, is accompanied by interference effects...

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  • A non-uniform real-time speech time-scale stretching method

    Publication

    An algorithm for non-uniform real-time speech stretching is presented. It provides a combination of typical SOLA algorithm (Synchronous Overlap and Add ) with the vowels, consonants and silence detectors. Based on the information about the content and the estimated value of the rate of speech (ROS), the algorithm adapts the scaling factor value. The ability of real-time speech stretching and the resultant quality of voice were...

  • Automatic sound recognition for security purposes

    Publication

    - Year 2008

    In the paper an automatic sound recognition system is presented. It forms a part of a bigger security system developed in order to monitor outdoor places for non-typical audio-visual events. The analyzed audio signal is being recorded from a microphone mounted in an outdoor place thus a non stationary noise of a significant energy is present in it. In the paper an especially designed algorithm for outdoor noise reduction is presented,...

  • Building Knowledge for the Purpose of Lip Speech Identification

    Consecutive stages of building knowledge for automatic lip speech identification are shown in this study. The main objective is to prepare audio-visual material for phonetic analysis and transcription. First, approximately 260 sentences of natural English were prepared taking into account the frequencies of occurrence of all English phonemes. Five native speakers from different countries read the selected sentences in front of...

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  • Recognition of Hand Drawn Flowcharts

    Publication

    - Year 2013

    In this paper the problem of hand drawn flowcharts recognition is presented. There are described two attitudes to this problem: on-line and off-line. A concept of FCE, a system for recognizing and understanding of freehand drawn on-line flow charts on desktop computer and mobile devices is presented. The first experiments with the FCE system and the planes for future are also described.

  • Semantic Integration of Heterogeneous Recognition Systems

    Publication

    - LECTURE NOTES IN COMPUTER SCIENCE - Year 2011

    Computer perception of real-life situations is performed using a variety of recognition techniques, including video-based computer vision, biometric systems, RFID devices and others. The proliferation of recognition modules enables development of complex systems by integration of existing components, analogously to the Service Oriented Architecture technology. In the paper, we propose a method that enables integration of information...

  • Communication Platform for Evaluation of Transmitted Speech Quality

    A voice communication system designed and implemented is described. The purpose of the presented platform was to enable a series of experiments related to the quality assessment of algorithms used in the coding and transmitting of speech. The system is equipped with tools for recording signals at each stage of processing, making it possible to subject them to subjective assessments by listening tests or, objective evaluation employing...

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  • Results of tests on speech intelligibility in reverberant conditions

    Open Research Data

    The dataset contains the results of tests that aimed to provide a relationship between the rate of speech (RoS) and reverberation conditions characterized by the Speech Transmission Index (STI).

  • Pitch estimation of narrowband-filtered speech signal using instantaneous complex frequency

    In this paper we propose a novel method of pitch estimation, based on instantaneous complex frequency (ICF). New iterative algorithm for analysis of ICF of speech signal in presented. Obtained results are compared with commonly used methods to prove its accuracy and connection between ICF and pitch, particularly for narrowband-filtered speech signal.

  • Pitch estimation of narrowband-filtered speech signal using instantaneous complex frequency

    Publication

    - Year 2007

    In this paper we propose a novel method of pitch estimation, based on instantaneous complex frequency (ICF). New iterative algorithm for analysis of ICF of speech signal in presented. Obtained results are compared with commonly used methods to prove its accuracy and connection between ICF and pitch, particularly for narrowband-filtered speech signal.

  • Automated detection of pronunciation errors in non-native English speech employing deep learning

    Publication

    - Year 2023

    Despite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...

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  • A Novel Method for Intelligibility Assessment of Nonlinearly Processed Speech in Spaces Characterized by Long Reverberation Times

    Publication

    Objective assessment of speech intelligibility is a complex task that requires taking into account a number of factors such as different perception of each speech sub-bands by the human hearing sense or different physical properties of each frequency band of a speech signal. Currently, the state-of-the-art method used for assessing the quality of speech transmission is the speech transmission index (STI). It is a standardized way...

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  • Emotion Space and Society

    Journals

    ISSN: 1755-4586 , eISSN: 1878-0040

  • Dependable Integration of Medical Image Recognition Components

    Computer driven medical image recognition may support medical doctors in the diagnosis process, but requires high dependability considering potential consequences of incorrect results. The paper presentsa system that improves dependability of medical image recognition by integration of results from redundant components. The components implement alternative recognition algorithms of diseases in thefield of gastrointestinal endoscopy....

  • Weakly-Supervised Word-Level Pronunciation Error Detection in Non-Native English Speech

    Publication
    • D. Korzekwa
    • J. Lorenzo-trueba
    • T. Drugman
    • S. Calamaro
    • B. Kostek

    - Year 2021

    We propose a weakly-supervised model for word-level mispronunciation detection in non-native (L2) English speech. To train this model, phonetically transcribed L2 speech is not required and we only need to mark mispronounced words. The lack of phonetic transcriptions for L2 speech means that the model has to learn only from a weak signal of word-level mispronunciations. Because of that and due to the limited amount of mispronounced...

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  • Feature extraction in detection and recognition of graphical objects

    Publication

    - Year 2022

    Detection and recognition of graphic objects in images are of great and growing importance in many areas, such as medical and industrial diagnostics, control systems in automation and robotics, or various types of security systems, including biometric security systems related to the recognition of the face or iris of the eye. In addition, there are all systems that facilitate the personal life of the blind people, visually impaired...

  • Guido: a musical score recognition system

    Publication

    - Year 2007

    This paper presents an optical music recognition system Guido that can automatically recognize the main musical symbols of music scores that were scanned or taken by a digital camera. The application is based on object model of musical notation and uses linguistic approach for symbol interpretation and error correction. The system offers musical editor with a partially automatic error correction.

  • Mowa nienawiści (hate speech) a odpowiedzialność dostawców usług internetowych w orzecznictwie sądów europejskich

    Publication

    - Year 2015

    The article analyses the phenomenon of hate speech in the Internet contrasted with the problem of responsability of Internet Service Providers for cases of such abuses of freedom of expression. The text provides an analysis of jurisprudence of two European Courts. On the one hand it presents the position of the European Court of Human Rights on the problem of hate speech: its definition and the liability for it as an exception...

  • Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition

    The article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...

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  • Objectivization of phonological evaluation of speech elements by means of audio parametrization

    This study addresses two issues related to both machine- and subjective-based speech evaluation by investigating five phonological phenomena related to allophone production. Its aim is to use objective parametrization and phonological classification of the recorded allophones. These allophones were selected as specifically difficult for Polish speakers of English: aspiration, final obstruent devoicing, dark lateral /l/, velar nasal...

  • Anion recognition by n,n'-diarylalkanediamides

    Publication

    The preparation of N,N'-diarylalkanediamides from respective aliphatic dicarboxylic acidesand 4-nitroaniline via microwave-promoted reactions is presented. The most positive effect of microwave irradiation was observed for N,N'-bis(4-nitrophenyl)butanediamide. Anion binding studies on the obtained diamides were carried out in DMSO and acetonitrile using UV-vis and 1H NMR spectroscopy. A mechanism for selective fluoride recognition...

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  • Elimination of clicks from archive speech signals using sparse autoregressive modeling

    Publication

    This paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear...

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  • Robust and Efficient Machine Learning Algorithms for Visual Recognition

    Publication

    - Year 2022

    In visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...

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  • AN ALGORITHM FOR PORTAL HYPERTENSIVE GASTROPATHY RECOGNITION ON THE ENDOSCOPIC RECORDINGS

    Publication

    Symptoms recognition of portal hypertensive gastropathy (PHG) can be done by analysing endoscopic recordings, but manual analysis done by physician may take a long time. This increases probability of missing some symptoms and automated methods may be applied to prevent that. In this paper a novel hybrid algorithm for recognition of early stage of portal hypertensive gastropathy is proposed. First image preprocessing is described....

  • Human-computer interactions in speech therapy using a blowing interface

    Publication

    In this paper we present a new human-computer interface for the quantitative measurement of blowing activities. The interface can measure the air flow and air pressure during the blowing activity. The measured values are stored and used to control the state of the graphical objects in the graphical user interface. In speech therapy children will find easier to play attractive therapeutic games than to perform repetitive and tedious,...

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  • Accelerometer signal pre-processing influence on human activity recognition

    A study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy.

  • Music Genre Recognition in the Rough Set-Based Environment

    Publication

    - Year 2015

    The aim of this paper is to investigate music genre recognition in the rough set-based environment. Experiments involve a parameterized music data-base containing 1100 music excerpts. The database is divided into 11 classes cor-responding to music genres. Tests are conducted using the Rough Set Exploration System (RSES), a toolset for analyzing data with the use of methods based on the rough set theory. Classification effectiveness...

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  • Speech and Drama

    Journals

    ISSN: 0038-7142

  • LANGUAGE AND SPEECH

    Journals

    ISSN: 0023-8309 , eISSN: 1756-6053

  • Hand gesture recognition supported by fuzzy rules and Kalman filters

    The paper presents a system based on camera and multimediaprojector enabling a user to control computer applications by dynamic hand gestures. Gesture recognition methodology based on representing hand movement trajectory by motion vectors analysed using fuzzy rule-based inference is first given. For effective hand position tracking Kalman filters are employed. The system engineered is developed using J2SE and C++/OpenCV technology....

  • Database of speech and facial expressions recorded with optimized face motion capture settings

    The broad objective of the present research is the analysis of spoken English employing a multiplicity of modalities. An important stage of this process, discussed in the paper, is creating a database of speech accompanied with facial expressions. Recordings of speakers were made using an advanced system for capturing facial muscle motion. A brief historical outline, current applications, limitations and the ways of capturing face...

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  • Study on Speech Transmission under Varying QoS Parameters in a OFDM Communication System

    Publication

    - Year 2021

    Although there has been an outbreak of multiple multimedia platforms worldwide, speech communication is still the most essential and important type of service. With the spoken word we can exchange ideas, provide descriptive information, as well as aid to another person. As the amount of available bandwidth continues to shrink, researchers focus on novel types of transmission, based most often on multi-valued modulations, multiple...

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  • Transfer learning in imagined speech EEG-based BCIs

    Publication

    - Biomedical Signal Processing and Control - Year 2019

    The Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...

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