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Search results for: SPEECH RECOGNITION SYSTEMS

  • Speech Analytics Based on Machine Learning

    Publication

    In this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...

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  • Examining Feature Vector for Phoneme Recognition

    Publication

    - Year 2018

    The aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...

  • Enhanced voice user interface employing spatial filtration of signals from acoustic vector sensor

    Spatial filtration of sound is introduced to enhance speech recognition accuracy in noisy conditions. An acoustic vector sensor (AVS) is employed. The signals from the AVS probe are processed in order to attenuate the surrounding noise. As a result the signal to noise ratio is increased. An experiment is featured in which speech signals are disturbed by babble noise. The signals before and after spatial filtration are processed...

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  • WYKORZYSTANIE SIECI NEURONOWYCH DO SYNTEZY MOWY WYRAŻAJĄCEJ EMOCJE

    Publication

    - Year 2018

    W niniejszym artykule przedstawiono analizę rozwiązań do rozpoznawania emocji opartych na mowie i możliwości ich wykorzystania w syntezie mowy z emocjami, wykorzystując do tego celu sieci neuronowe. Przedstawiono aktualne rozwiązania dotyczące rozpoznawania emocji w mowie i metod syntezy mowy za pomocą sieci neuronowych. Obecnie obserwuje się znaczny wzrost zainteresowania i wykorzystania uczenia głębokiego w aplikacjach związanych...

  • Separability Assessment of Selected Types of Vehicle-Associated Noise

    Music Information Retrieval (MIR) area as well as development of speech and environmental information recognition techniques brought various tools in-tended for recognizing low-level features of acoustic signals based on a set of calculated parameters. In this study, the MIRtoolbox MATLAB tool, designed for music parameter extraction, is used to obtain a vector of parameters to check whether they are suitable for separation of...

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  • Bimodal classification of English allophones employing acoustic speech signal and facial motion capture

    A method for automatic transcription of English speech into International Phonetic Alphabet (IPA) system is developed and studied. The principal objective of the study is to evaluate to what extent the visual data related to lip reading can enhance recognition accuracy of the transcription of English consonantal and vocalic allophones. To this end, motion capture markers were placed on the faces of seven speakers to obtain lip...

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  • Noise profiling for speech enhancement employing machine learning models

    Publication

    - Journal of the Acoustical Society of America - Year 2022

    This paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...

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  • Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review

    Publication

    - SENSORS - Year 2022

    The automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities...

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  • Examining Feature Vector for Phoneme Recognition / Analiza parametrów w kontekście automatycznej klasyfikacji fonemów

    Publication

    - Year 2017

    The aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...

  • Mispronunciation Detection in Non-Native (L2) English with Uncertainty Modeling

    Publication

    - Year 2021

    A common approach to the automatic detection of mispronunciation in language learning is to recognize the phonemes produced by a student and compare it to the expected pronunciation of a native speaker. This approach makes two simplifying assumptions: a) phonemes can be recognized from speech with high accuracy, b) there is a single correct way for a sentence to be pronounced. These assumptions do not always hold, which can result...

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  • Selection of Features for Multimodal Vocalic Segments Classification

    Publication

    English speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...

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  • Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training

    Publication

    In the paper we tackle bi-objective execution time and power consumption optimization problem concerning execution of parallel applications. We propose using a discrete-event simulation environment for exploring this power/time trade-off in the form of a Pareto front. The solution is verified by a case study based on a real deep neural network training application for automatic speech recognition. A simulation lasting over 2 hours...

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  • Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging

    Publication

    In the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...

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  • Zastosowanie metod eksploracji danych do analizy odpowiedzi czujników gazu

    Publication

    - Year 2018

    Zagadnienia poruszane w niniejszej rozprawie dotyczą zastosowania metod eksploracji danych do analizy odpowiedzi czujników gazu, umożliwiających poprawną identyfikację składu mieszaniny gazowej w elektronicznych systemach rozpoznawania gazu. Elektroniczne systemy rozpoznawania gazu to urządzenia wykorzystujące czujniki gazu oraz odpowiednio dobrane metody analizy danych pomiarowych, zdolne do określenia składu mierzonej mieszaniny...

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  • Performance Analysis of the OpenCL Environment on Mobile Platforms

    Publication

    Today’s smartphones have more and more features that so far were only assigned to personal computers. Every year these devices are composed of better and more efficient components. Everything indicates that modern smartphones are replacing ordinary computers in various activities. High computing power is required for tasks such as image processing, speech recognition and object detection. This paper analyses the performance of...

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  • Towards More Realistic Probabilistic Models for Data Structures: The External Path Length in Tries under the Markov Model

    Publication

    - Year 2013

    Tries are among the most versatile and widely used data structures on words. They are pertinent to the (internal) structure of (stored) words and several splitting procedures used in diverse contexts ranging from document taxonomy to IP addresses lookup, from data compression (i.e., Lempel- Ziv'77 scheme) to dynamic hashing, from partial-match queries to speech recognition, from leader election algorithms to distributed hashing...

  • Computer-assisted pronunciation training—Speech synthesis is almost all you need

    Publication

    - SPEECH COMMUNICATION - Year 2022

    The research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...

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  • Evaluation of Lombard Speech Models in the Context of Speech in Noise Enhancement

    Publication

    - IEEE Access - Year 2020

    The Lombard effect is one of the most well-known effects of noise on speech production. Speech with the Lombard effect is more easily recognizable in noisy environments than normal natural speech. Our previous investigations showed that speech synthesis models might retain Lombard-effect characteristics. In this study, we investigate several speech models, such as harmonic, source-filter, and sinusoidal, applied to Lombard speech...

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  • Akustyczna analiza natężenia ruchu drogowego dla systemów zarządzania ruchem

    Publication

    - Year 2019

    W pracy przybliżono wybrane zagadnienia z dziedziny zarządzania transportem drogowym w Polsce i na świecie. W tym kontekście pzredstawiono potrzeby rynkowe, wymagania jak i możliwości w zakresie pozyskiwania informacji o aktualnym stanie sieci drogowych. Zaproponowano akustyczną metodę nadzorowania ruchu drogowego i jej możliwości w kontekście systemów zarządzania ruchem. Przedstawiono schemat akwizycji sygnału wraz z danymi odniesienia....

  • Speech Intelligibility Measurements in Auditorium

    Publication

    Speech intelligibility was measured in Auditorium Novum on Technical University of Gdansk (seating capacity 408, volume 3300 m3). Articulation tests were conducted; STI and Early Decay Time EDT coefficients were measured. Negative noise contribution to speech intelligibility was taken into account. Subjective measurements and objective tests reveal high speech intelligibility at most seats in auditorium. Correlation was found between...

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  • Detecting Lombard Speech Using Deep Learning Approach

    Publication
    • K. Kąkol
    • G. Korvel
    • G. Tamulevicius
    • B. Kostek

    - SENSORS - Year 2023

    Robust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...

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  • Transient detection for speech coding applications

    Signal quality in speech codecs may be improved by selecting transients from speech signal and encoding them using a suitable method. This paper presents an algorithm for transient detection in speech signal. This algorithm operates in several frequency bands. Transient detection functions are calculated from energy measured in short frames of the signal. The final selection of transient frames is based on results of detection...

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  • Improving the quality of speech in the conditions of noise and interference

    Publication

    The aim of the work is to present a method of intelligent modification of the speech signal with speech features expressed in noise, based on the Lombard effect. The recordings utilized sets of words and sentences as well as disturbing signals, i.e., pink noise and the so-called babble speech. Noise signal, calibrated to various levels at the speaker's ears, was played over two loudspeakers located 2 m away from the speaker. In...

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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...

  • Applying the Lombard Effect to Speech-in-Noise Communication

    Publication

    - Electronics - Year 2023

    This study explored how the Lombard effect, a natural or artificial increase in speech loudness in noisy environments, can improve speech-in-noise communication. This study consisted of several experiments that measured the impact of different types of noise on synthesizing the Lombard effect. The main steps were as follows: first, a dataset of speech samples with and without the Lombard effect was collected in a controlled setting;...

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  • Constructing a Dataset of Speech Recordingswith Lombard Effect

    Publication

    - Year 2020

    Thepurpose of therecordings was to create a speech corpus based on the ISLEdataset, extended with video and Lombard speech. Selected from a set of 165sentences, 10, evaluatedas having thehighest possibility to occur in the context ofthe Lombard effect,were repeated in the presence of the so-called babble speech to obtain Lombard speech features. Altogether,15speakers were recorded, and speech parameterswere...

  • 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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  • Improved method for real-time speech stretching

    Publication

    n algorithm for real-time speech stretching is presented. It was designed to modify input signal dependently on its content and on its relation with the historical input data. The proposed algorithm is a combination of speech signal analysis algorithms, i.e. voice, vowels/consonants, stuttering detection and SOLA (Synchronous-Overlap-and-Add) based speech stretching algorithm. This approach enables stretching input speech signal...

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  • 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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  • Real-time speech-rate modification experiments

    Publication

    An algorithm designed for real-time speech time scale modification (stretching) is proposed, providing a combination of typical synchronous overlap and add based time scale modification algorithm and signal redundancy detection algorithms that allow to remove parts of the speech signal and replace them with the stretched speech signal fragments. Effectiveness of signal processing algorithms are examined experimentally together...

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  • Koncepcja analizy stanów emocjonalnych użytkowników w kontekście systemów zabezpieczeń transportowych

    Autorzy, przywołując własne i światowe badania nad rozpoznawaniem emocji ludzkich z obrazu twarzy, wskazują na możliwość zastosowania algorytmów komputerowych i ich implementacji w komputerach osobistych (i innych urządzeniach personalnych wyposażonych w dostatecznie silny procesor obliczeniowy). Zastosowanie takiego rozwiązania może poprawić bezpieczeństwo użytkowania urządzeń, maszyn i pojazdów, których operatorzy muszą gwarantować...

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  • Improving Objective Speech Quality Indicators in Noise Conditions

    Publication

    - Year 2020

    This work aims at modifying speech signal samples and test them with objective speech quality indicators after mixing the original signals with noise or with an interfering signal. Modifications that are applied to the signal are related to the Lombard speech characteristics, i.e., pitch shifting, utterance duration changes, vocal tract scaling, manipulation of formants. A set of words and sentences in Polish, recorded in silence,...

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  • Emotion Recognition for Affect Aware Video Games

    In this paper the idea of affect aware video games is presented. A brief review of automatic multimodal affect recognition of facial expressions and emotions is given. The first result of emotions recognition using depth data as well as prototype affect aware video game are presented

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  • Emotion Recognition and Its Applications

    The paper proposes a set of research scenarios to be applied in four domains: software engineering, website customization, education and gaming. The goal of applying the scenarios is to assess the possibility of using emotion recognition methods in these areas. It also points out the problems of defining sets of emotions to be recognized in different applications, representing the defined emotional states, gathering the data and...

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  • 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,...

  • Speech synthesis controlled by eye gazing

    Publication

    - Year 2010

    A method of communication based on eye gaze controlling is presented. Investigations of using gaze tracking have been carried out in various context applications. The solution proposed in the paper could be referred to as ''talking by eyes'' providing an innovative approach in the domain of speech synthesis. The application proposed is dedicated to disabled people, especially to persons in a so-called locked-in syndrome who cannot...

  • Acoustic Sensing Analytics Applied to Speech in Reverberation Conditions

    Publication

    The paper aims to discuss a case study of sensing analytics and technology in acoustics when applied to reverberation conditions. Reverberation is one of the issues that makes speech in indoor spaces challenging to understand. This problem is particularly critical in large spaces with few absorbing or diffusing surfaces. One of the natural remedies to improve speech intelligibility in such conditions may be achieved through speaking...

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  • Time-domain prosodic modifications for text-to-speech synthesizer

    Publication

    - Year 2010

    An application of prosodic speech processing algorithms to Text-To-Speech synthesis is presented. Prosodic modifications that improve the naturalness of the synthesized signal are discussed. The applied method is based on the TD-PSOLA algorithm. The developed Text-To-Speech Synthesizer is used in applications employing multimodal computer interfaces.

  • A Method of Real-Time Non-uniform Speech Stretching

    Publication

    Developed method of real-time non-uniform speech stretching is presented.The proposed solution is based on the well-known SOLA algorithm(Synchronous Overlap and Add). Non-uniform time-scale modification isachieved by the adjustment of time scaling factor values in accordance with thesignal content. Dependently on the speech unit (vowels/consonants), instantaneousrate of speech (ROS), and speech signal presence, values of the scalingfactor...

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  • 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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  • 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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  • Uncertainty in emotion recognition

    Purpose–The purpose of this paper is to explore uncertainty inherent in emotion recognition technologiesand the consequences resulting from that phenomenon.Design/methodology/approach–The paper is a general overview of the concept; however, it is basedon a meta-analysis of multiple experimental and observational studies performed over the past couple of years.Findings–The mainfinding of the paper might be summarized as follows:...

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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...

  • 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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  • 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...

  • Rough Sets Applied to Mood of Music Recognition

    Publication

    - Year 2016

    With the growth of accessible digital music libraries over the past decade, there is a need for research into automated systems for searching, organizing and recommending music. Mood of music is considered as one of the most intuitive criteria for listeners, thus this work is focused on the emotional content of music and its automatic recognition. The research study presented in this work contains an attempt to music emotion recognition...