Wyniki wyszukiwania dla: AUDIO-VISUAL SPEECH RECOGNITION - MOST Wiedzy

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Wyniki wyszukiwania dla: AUDIO-VISUAL SPEECH RECOGNITION

Wyniki wyszukiwania dla: AUDIO-VISUAL SPEECH RECOGNITION

  • Biometria i przetwarzanie mowy 2024

    Kursy Online
    • J. Daciuk

    {mlang pl} Celem kursu jest zapoznanie studentów z: metodami ustalania i potwierdzania tożsamości ludzi na podstawie mierzalnych cech organizmu cechami mowy ludzkiej, w szczególności polskiej metodami rozpoznawania mowy metodami syntezy mowy {mlang} {mlang en} The aim of the course is to familiarize the students with: methods of identification and verification of identity of people based on measurable features of their...

  • Ranking Speech Features for Their Usage in Singing Emotion Classification

    Publikacja

    This paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...

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  • SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM

    The main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...

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  • Acceleration of decision making in sound event recognition employing supercomputing cluster

    Parallel processing of audio data streams is introduced to shorten the decision making time in hazardous sound event recognition. A supercomputing cluster environment with a framework dedicated to processing multimedia data streams in real time is used. The sound event recognition algorithms employed are based on detecting foreground events, calculating their features in short time frames, and classifying the events with Support...

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  • Variable Ratio Sample Rate Conversion Based on Fractional Delay Filter

    Publikacja

    - Archives of Acoustics - Rok 2014

    In this paper a sample rate conversion algorithm which allows for continuously changing resampling ratio has been presented. The proposed implementation is based on a variable fractional delay filter which is implemented by means of a Farrow structure. Coefficients of this structure are computed on the basis of fractional delay filters which are designed using the offset window method. The proposed approach allows us to freely...

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  • Using Physiological Signals for Emotion Recognition

    Publikacja

    - Rok 2013

    Recognizing user’s emotions is the promising area of research in a field of human-computer interaction. It is possible to recognize emotions using facial expression, audio signals, body poses, gestures etc. but physiological signals are very useful in this field because they are spontaneous and not controllable. In this paper a problem of using physiological signals for emotion recognition is presented. The kinds of physiological...

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  • PHONEME DISTORTION IN PUBLIC ADDRESS SYSTEMS

    Publikacja

    The quality of voice messages in speech reinforcement and public address systems is often poor. The sound engineering projects of such systems take care of sound intensity and possible reverberation phenomena in public space without, however, considering the influence of acoustic interference related to the number and distribution of loudspeakers. This paper presents the results of measurements and numerical simulations of the...

  • Discovering Rule-Based Learning Systems for the Purpose of Music Analysis

    Publikacja

    Music analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...

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  • Marking the Allophones Boundaries Based on the DTW Algorithm

    Publikacja

    - Rok 2018

    The paper presents an approach to marking the boundaries of allophones in the speech signal based on the Dynamic Time Warping (DTW) algorithm. Setting and marking of allophones boundaries in continuous speech is a difficult issue due to the mutual influence of adjacent phonemes on each other. It is this neighborhood on the one hand that creates variants of phonemes that is allophones, and on the other hand it affects that the border...

  • In uence of Low-Level Features Extracted from Rhythmic and Harmonic Sections on Music Genre Classi cation

    Publikacja

    - Rok 2013

    We present a comprehensive evaluation of the infuence of 'harmonic' and rhythmic sections contained in an audio file on automatic music genre classi cation. The study is performed using the ISMIS database composed of music files, which are represented by vectors of acoustic parameters describing low-level music features. Non-negative Matrix Factorization serves for blind separation of instrument components. Rhythmic components...

  • Classifying type of vehicles on the basis of data extracted from audio signal characteristics

    The aim of this study is to find and optimize a feature vector for an automatic recognition of the type of vehicles, extracted form an audio signal. First, the influence of weather-based conditions of road surface on spectral characteristic of the audio signal recorded from a passing vehicle in close proximity to the road is discussed. Next, parameterization of the recorded audio signal is performed. For that purpose, the MIRtoolbox,...

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  • Subjective and Objective Comparative Study of DAB+ Broadcast System

    Broadcasting services seek to optimize their use of bandwidth in order to maximize user’s quality of experience. They aim to transmit high-quality digital speech and music signals at the lowest bitrate. They intend to offer the best quality under available conditions. Due to bandwidth limitations, audio quality is in conflict with the number of transmitted radio programs. This paper analyzes whether the quality of real-time digital...

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  • Deep neural networks for data analysis

    Kursy Online
    • K. Draszawka

    The aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...

  • Szymon Andrzejewski dr

    Ukończył Uniwersytet Gdański na kierunku Politologia, specjalizacja ustrojowo-samorządowa w 2008 roku. Ukończył studia podyplomowe na Politechnice Gdańskiej pod nazwą "Zarządzanie i ewaluacja projektów finansowanych z funduszy Unii Europejskiej" w 2010r. i na Akademii Górniczo-Hutniczej pod nazwą "Ochrona Środowiska przed hałasem i drganiami" w 2012 roku. Student Socjologicznych Studiów Doktoranckich na Uniwersytecie Gdańskim od...

  • Recognition of hazardous acoustic events employing parallel processing on a supercomputing cluster . Rozpoznawanie niebezpiecznych zdarzeń dźwiękowych z wykorzystaniem równoległego przetwarzania na klastrze superkomputerowym

    Publikacja

    A method for automatic recognition of hazardous acoustic events operating on a super computing cluster is introduced. The methods employed for detecting and classifying the acoustic events are outlined. The evaluation of the recognition engine is provided: both on the training set and using real-life signals. The algorithms yield sufficient performance in practical conditions to be employed in security surveillance systems. The...

  • Rough Sets Applied to Mood of Music Recognition

    Publikacja

    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...

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

    Publikacja

    - Rok 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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  • Gesture-controlled Sound Mixing System With a Sonified Interface

    Publikacja

    - Rok 2013

    In this paper the Authors present a novel approach to sound mixing. It is materialized in a system that enables to mix sound with hand gestures recognized in a video stream. The system has been developed in such a way that mixing operations can be performed both with or without visual support. To check the hypothesis that the mixing process needs only an auditory display, the influence of audio information visualization on sound...

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  • Examining Feature Vector for Phoneme Recognition

    Publikacja

    - Rok 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...

  • 1D convolutional context-aware architectures for acoustic sensing and recognition of passing vehicle type

    Publikacja

    A network architecture that may be employed to sensing and recognition of a type of vehicle on the basis of audio recordings made in the proximity of a road is proposed in the paper. The analyzed road traffic consists of both passenger cars and heavier vehicles. Excerpts from recordings that do not contain vehicles passing sounds are also taken into account and marked as ones containing silence....

  • Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System

    The main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...

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  • Creating a Realible Music Discovery and Recomendation System

    The aim of this paper is to show problems related to creating a reliable music dis-covery system. The SYNAT database that contains audio files is used for the purpose of experiments. The files are divided into 22 classes corresponding to music genres with different cardinality. Of utmost importance for a reliable music recommendation system are the assignment of audio files to their appropriate gen-res and optimum parameterization...

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  • Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing

    Developing signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....

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  • Remote Estimation of Video-Based Vital Signs in Emotion Invocation Studies

    Abstract— The goal of this study is to examine the influence of various imitated and video invoked emotions on the vital signs (respiratory and pulse rates). We also perform an analysis of the possibility to extract signals from sequences acquired with cost-effective cameras. The preliminary results show that the respiratory rate allows for better separation of some emotions than the pulse rate, yet this relation highly depends...

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  • Estimation of the short-term predictor parameters of speech under noisy conditions

    Publikacja

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  • Elimination of Impulsive Disturbances From Stereo Audio Recordings Using Vector Autoregressive Modeling and Variable-order Kalman Filtering

    This paper presents a new approach to elimination of impulsive disturbances from stereo audio recordings. The proposed solution is based on vector autoregressive modeling of audio signals. Online tracking of signal model parameters is performed using the exponential ly weighted least squares algo- rithm. Detection of noise pulses an d model-based interpolation of the irrevocably distorted sampl es is realized using an adaptive, variable-order...

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  • Elimination of Impulsive Disturbances From Archive Audio Signals Using Bidirectional Processing

    In this application-oriented paper we consider the problem of elimination of impulsive disturbances, such as clicks, pops and record scratches, from archive audio recordings. The proposed approach is based on bidirectional processing—noise pulses are localized by combining the results of forward-time and backward-time signal analysis. Based on the results of specially designed empirical tests (rather than on the results of theoretical analysis),...

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  • Dynamic Bayesian Networks for Symbolic Polyphonic Pitch Modeling

    Publikacja

    Symbolic pitch modeling is a way of incorporating knowledge about relations between pitches into the process of an- alyzing musical information or signals. In this paper, we propose a family of probabilistic symbolic polyphonic pitch models, which account for both the “horizontal” and the “vertical” pitch struc- ture. These models are formulated as linear or log-linear interpo- lations of up to fi ve sub-models, each of which is...

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  • Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation

    In this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic model,...

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  • New approach for determining the QoS of MP3-coded voice signals in IP networks

    Publikacja

    Present-day IP transport platforms being what they are, it will never be possible to rule out conflicts between the available services. The logical consequence of this assertion is the inevitable conclusion that the quality of service (QoS) must always be quantifiable no matter what. This paper focuses on one method to determine QoS. It defines an innovative, simple model that can evaluate the QoS of MP3-coded voice data transported...

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  • Automatic music signal mixing system based on one-dimensional Wave-U-Net autoencoders

    The purpose of this paper is to show a music mixing system that is capable of automatically mixing separate raw recordings with good quality regardless of the music genre. This work recalls selected methods for automatic audio mixing first. Then, a novel deep model based on one-dimensional Wave-U-Net autoencoders is proposed for automatic music mixing. The model is trained on a custom-prepared database. Mixes created using the...

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  • Robust Object Detection with Multi-input Multi-output Faster R-CNN

    Publikacja

    Recent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...

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  • Robust Object Detection with Multi-input Multi-output Faster R-CNN

    Publikacja

    Recent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...

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  • Bimodal Emotion Recognition Based on Vocal and Facial Features

    Emotion recognition is a crucial aspect of human communication, with applications in fields such as psychology, education, and healthcare. Identifying emotions accurately is challenging, as people use a variety of signals to express and perceive emotions. In this study, we address the problem of multimodal emotion recognition using both audio and video signals, to develop a robust and reliable system that can recognize emotions...

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  • Music genre classification applied to bass enhancement for mobile technology

    The aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) algorithms applied to portable computers. The proposed algorithm is related to intelligent, rule-based setting of synthesis parameters according to music genre of an audio excerpt. The classification of music genres is automatically executed employing MPEG 7 parameters and the Principal Component Analysis method applied to reduce information...

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  • Using Eye-tracking to get information on the skills acquisition by the radiology residents

    This paper describes the possibility of monitoring the progress of knowledge and skills acquisition by the students of radiology. It is achieved by an analysis of a visual attention distribution patterns during image-based tasks solving. The concept is to use the eye-tracking data to recognize the way how the radiographic images are read by recognized experts, radiography residents involved in the training program, and untrained...

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  • Video Semantic Analysis Framework based on Run-time Production Rules - Towards Cognitive Vision

    Publikacja

    This paper proposes a service-oriented architecture for video analysis which separates object detection from event recognition. Our aim is to introduce new tools to be considered in the pathway towards Cognitive Vision as a support for classical Computer Vision techniques that have been broadly used by the scientific community. In the article, we particularly focus in solving some of the reported scalability issues found in current...

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  • Application of gaze tracking technology to quality of experience domain

    Publikacja

    - Rok 2010

    A new methodological approach to study subjective assessment results employing gaze tracking technology is shown. Notions of Human-Computer Interaction (HCI) and Quality of Experience (QoE) are shortly introduced in the context of their common application. Then, the gaze tracking system developed at the Multimedia Systems Department (MSD) of Gdansk University of Technology (GUT) is presented. A series of audio-visual subjective...

  • Audio Content and Crowdsourcing: A Subjective Quality Evaluation of Radio Programs Streamed Online

    Publikacja

    - Rok 2023

    Radio broadcasting has been present in our lives for over 100 years. The transmission of speech and music signals accompanies us from an early age. Broadcasts provide the latest information from home and abroad. They also shape musical tastes and allow many artists to share their creativity. Modern distribution involves transmission over a number of terrestrial systems. The most popular are analog FM (Frequency Modulation) and...

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  • Quality Analysis of Audio-Video Transmission in an OFDM-Based Communication System

    Publikacja

    - Rok 2022

    Application of a reliable audio-video communication system, brings many advantages. With the spoken word we can exchange ideas, provide descriptive information, as well as aid to another person. With the availability of visual information one can monitor the surrounding, working environment, etc. As the amount of available bandwidth continues to shrink, researchers focus on novel types of transmission. Currently, orthogonal frequency...

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  • Orken Mamyrbayev Professor

    Osoby

    1.  Education: Higher. In 2001, graduated from the Abay Almaty State University (now Abay Kazakh National Pedagogical University), in the specialty: Computer science and computerization manager. 2.  Academic degree: Ph.D. in the specialty "6D070300-Information systems". The dissertation was defended in 2014 on the topic: "Kazakh soileulerin tanudyn kupmodaldy zhuyesin kuru". Under my supervision, 16 masters, 1 dissertation...

  • On the Consumption of Multimedia Content Using Mobile Devices: a Year to Year User Case Study

    Publikacja

    In the early days, consumption of multimedia content related with audio signals was only possible in a stationary manner. The music player was located at home, with a necessary physical drive. An alternative way for an individual was to attend a live performance at a concert hall or host a private concert at home. To sum up, audio-visual effects were only reserved for a narrow group of recipients. Today, thanks to portable players,...

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

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

    Publikacja

    - Rok 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...

  • Voice command recognition using hybrid genetic algorithm

    Publikacja

    Abstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...

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  • Quality Evaluation of Novel DTD Algorithm Based on Audio Watermarking

    Publikacja

    Echo cancellers typically employ a doubletalk detection (DTD) algorithm in order to keep the adaptive filter from diverging in the presence of near-end speech signal or other disruptive sounds in the microphone signal. A novel doubletalk detection algorithm based on techniques similar to those used for audio signal watermarking was introduced by the authors. The application of the described DTD algorithm within acoustic echo cancellation...

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  • Audio content analysis in the urban area telemonitoring system

    Publikacja

    Artykuł przedstawia możliwości rozwinięcie monitoringu miejskiego o automatyczną analizę dźwięku. Przedstawiono metody parametryzacji dźwięku, które możliwe są do zastosowania w takim systemie oraz omówiono aspekty techniczne implementacji. W kolejnej części przedstawiono system decyzyjny oparty na drzewach zastosowany w systemie. System ten rozpoznaje dźwięki niebezpieczne (strzał, rozbita szyba, krzyk) wśród dźwięków zarejestrowanych...

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  • Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations

    Publikacja

    An evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...

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  • Further developments of parameterization methods of audio stream analysis for secuirty purposes

    Publikacja

    - Rok 2009

    The paper presents an automatic sound recognition algorithm intended for application in an audiovisual security monitoring system. A distributed character of security systems does not allow for simultaneous observation of multiple multimedia streams, thus an automatic recognition algorithm must be introduced. In the paper, a module for the parameterization and automatic detection of audio events is described. The spectral analyses...

  • Digital Transformation of Terrestrial Radio: An Analysis of Simulcasted Broadcasts in FM and DAB+ for a Smart and Successful Switchover

    The process of digitizing radio is far from over. It is an important interdisciplinary aspect, involving Big Data and AI (Artificial Intelligence) when it comes to classifying and handling content, and an organizational challenge in the Industry 4.0 concept. There exist several methods for delivering audio signals, including terrestrial broadcasting and internet streaming. Among them, the DAB+ (Digital Audio Broadcasting plus)...

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