Audiovisual Model Research Articles

Emotion and attention: Audiovisual models for group-level skin response recognition in short movies

Emotion and attention: Audiovisual models for group-level skin response recognition in short movies

Audio-visual networks and the road to 5G

Multiple upcoming 5G use-cases seem to particularly depend on network deployment and role model questions. Service reliability, liability and ultimately adequate licensing of spectrum are likely to be the primary success factors, independent of features to be implemented in 5G new radio. Here, this article discusses standardization enabling different audio-visual production use-cases and flexible models within the 5G system.

Improving Student Listening Ability Through Audio-Visual Application At Smpn 2 Painan

To learn a lesson well, we need to hear, see, ask questions about it, and discuss it with others. Not only that, teachers need to "do it", that is to describe something in their own way, to show their example, to try to practice their skills and to do tasks that demand the knowledge they have gained.Problems that want to be studied in this research are: Is using Audio-Visual model in students of class IX SMP Negeri 2 Painan year 2015 – 2016. Steps in using the Audio-Visual implementation method? This research was conducted in class VII of SMP Negeri 1 Painan. This place was chosen because based on the results of class observations and interviews with English teachers in the classroom it can be concluded that the skills of students listening in English is still low. This is because teachers do not use adequate techniques, limited books that are in school and media equipment is still lacking. Research time. This research was conducted from early October as a description of the implementation of this study can be seen in the following table: This stage is intended to thoroughly review the actions that have been done, based on data that has accumulated in the previous step. And look for difficulties experienced by students and teachers in the process of action that has been done. Students are invited to discuss each cycle to ask about their difficulties. The teacher reflects on past events as the process of action takes place. All the data obtained are analyzed and evaluated to refine the action in the next cycle or whether or not the treatment given to the students is continued. By knowing that the triggers of low learning activity and learning achievement are in factors such as the method used by the teacher, so the use or replacement of conventional methods into constructivist methods is indispensable, consequently the researchers tried the Audio-Visual learning model in an attempt to solve problems at school. Based on the low learning activities and student achievement that are presented on the background of the problem, the use of Audio-Visual learning model attempted to be able to complete the purpose of this research is to know the improvement of student achievement. How much improvement has been made clear at the end of the analysis. From the results of the research presented in Chapter IV and all the data that have been submitted, the research objectives submitted can already be achieved. To answer the purpose of research is the achievement of student prestai achievement can be seen evidence that has been submitted. From the baseline data almost all students got the score below, then in cycle I decreased to 8 students and cycle II scores all students above the standard specified in the school. From the initial average of 4.5 increased to 6.3 in cycle I and on the second cycle rose to 7.9. From the initial data no students are complete while in cycle I become more that 4 students and on cycle II all students reach mastery.From all supporting data proving the achievement of learning objectives can be submitted that Audio-Visual model can give the expected answers according to the purpose of this study. All this can be achieved is due to the readiness and hard work of researchers from the time of making the proposal, review the things that have not been good with friends of teachers, preparation of grids and research instruments, the use of means of data triangulation to the implementation of the maximum research.

Looking to listen at the cocktail party

We present a joint audio-visual model for isolating a single speech signal from a mixture of sounds such as other speakers and background noise. Solving this task using only audio as input is extremely challenging and does not provide an association of the separated speech signals with speakers in the video. In this paper, we present a deep network-based model that incorporates both visual and auditory signals to solve this task. The visual features are used to "focus" the audio on desired speakers in a scene and to improve the speech separation quality. To train our joint audio-visual model, we introduce AVS peech , a new dataset comprised of thousands of hours of video segments from the Web. We demonstrate the applicability of our method to classic speech separation tasks, as well as real-world scenarios involving heated interviews, noisy bars, and screaming children, only requiring the user to specify the face of the person in the video whose speech they want to isolate. Our method shows clear advantage over state-of-the-art audio-only speech separation in cases of mixed speech. In addition, our model, which is speaker-independent (trained once, applicable to any speaker), produces better results than recent audio-visual speech separation methods that are speaker-dependent (require training a separate model for each speaker of interest).

Retraining speech production and fluency in non-fluent/agrammatic primary progressive aphasia.

The non-fluent/agrammatic variant of primary progressive aphasia (nfvPPA) presents with a gradual decline in grammar and motor speech resulting from selective degeneration of speech-language regions in the brain. There has been considerable progress in identifying treatment approaches to remediate language deficits in other primary progressive aphasia variants; however, interventions for the core deficits in nfvPPA have yet to be systematically investigated. Further, the neural mechanisms that support behavioural restitution in the context of neurodegeneration are not well understood. We examined the immediate and long-term benefits of video implemented script training for aphasia (VISTA) in 10 individuals with nfvPPA. The treatment approach involved repeated rehearsal of individualized scripts via structured treatment with a clinician as well as intensive home practice with an audiovisual model using 'speech entrainment'. We evaluated accuracy of script production as well as overall intelligibility and grammaticality for trained and untrained scripts. These measures and standardized test scores were collected at post-treatment and 3-, 6-, and 12-month follow-up visits. Treatment resulted in significant improvement in production of correct, intelligible scripted words for trained topics, a reduction in grammatical errors for trained topics, and an overall increase in intelligibility for trained as well as untrained topics at post-treatment. Follow-up testing revealed maintenance of gains for trained scripts up to 1 year post-treatment on the primary outcome measure. Performance on untrained scripts and standardized tests remained relatively stable during the follow-up period, indicating that treatment helped to stabilize speech and language despite disease progression. To identify neural predictors of responsiveness to intervention, we examined treatment effect sizes relative to grey matter volumes in regions of interest derived from a previously identified speech production network. Regions of significant atrophy within this network included bilateral inferior frontal cortices and supplementary motor area as well as left striatum. Volumes in a left middle/inferior temporal region of interest were significantly correlated with the magnitude of treatment effects. This region, which was relatively spared anatomically in nfvPPA patients, has been implicated in syntactic production as well as visuo-motor facilitation of speech. This is the first group study to document the benefits of behavioural intervention that targets both linguistic and motoric deficits in nfvPPA. Findings indicate that behavioural intervention may result in lasting and generalized improvement of communicative function in individuals with neurodegenerative disease and that the integrity of spared regions within the speech-language network may be an important predictor of treatment response.

Analysis of a Pediatric Telemedicine Program.

Telemedicine serves millions of patients and is transforming healthcare delivery worldwide. In October of 2015, Nemours Children's Health System began offering direct-to-consumer (DTC) pediatric telemedicine on the Nemours CareConnect (NCC) platform. Currently, there are no descriptive data available on pediatric-specific DTC 24/7 programs. This is the first article to our knowledge that provides data on such a program. A retrospective data analysis of the first 1,000 visits was conducted. All patient data were precollected and deidentified. NCC was accessed for skin-related concerns (18.7%), upper respiratory symptoms (17.5%), fever (15.2%), and gastrointestinal issues (9.7%) most often on Saturdays and Sundays. Patients' ages ranged from 2 weeks to 20 years with the median age of 4 years. The peak time of call was between 4:00 PM and 8:00 PM. Median visit wait time was 2 min 11 s and median treatment time was 12 min 10 s. Patients rated providers and the NCC platform using a 5-star rating system. Over 93% of patients rated providers 5 stars and 86.0% rated the NCC platform 5 stars. Sixty-seven percent of parents reported they would have accessed an urgent care center, emergency room, or retail clinic if NCC were not available. NCC provides accessible, efficient care and parents are satisfied with the service. The postvisit survey suggested parents would have sought more expensive care if NCC were not available. NCC provided descriptive data using an audiovisual model. NCC warrants further investigation in regard to redirection of services.

PENGGUNAAN MEDIA AUDIOVISUAL UNTUK MENINGKATKAN HASIL BELAJAR SISWA DALAM MATA PELAJARAN MEMBIAKAN TANAMAN DENGAN BIJI JURUSAN AGRIBISNIS PEMBIBITAN DAN KULTUR JARINGAN KELAS X DI SMK NEGERI 4 JENEPONTO

The goal of this research is to improve plant breeding learning activities using audiovisual media to improve the learning outcomes of students studying plant breeding with seeds using audiovisual media. The method used for this research is classroom action research. Data are acquired through observations, interviews and research questionnaire. Technique of data analysis used is descriptive quantitative and qualitative. The use of audiovisual media spurs students to be more enthusiastic during lessons because audiovisual media has an appealing factor in that it uses real pictures that can be seen and heard. The results of this research shows that using the audiovisual leeson model has a significant contribution in increasing activeness in learning and learning achievement. This shows that audiovisual media learning can be used while learning because the learners’ target has been reached according to the criterion.

Cross-modal processing of voices and faces in developmental prosopagnosia and developmental phonagnosia

ABSTRACTConspecifics can be recognized from either the face or the voice alone. However, person identity information is rarely encountered in purely unimodal situations and there is increasing evidence that the face and voice interact in neurotypical identity processing. Conversely, developmental deficits have been observed that seem to be selective for face and voice recognition, developmental prosopagnosia and developmental phonagnosia, respectively. To date, studies on developmental prosopagnosia and phonagnosia have largely centred on within modality testing. Here, we review evidence from a small number of behavioural and neuroimaging studies which have examined the recognition of both faces and voices in these cohorts. A consensus from the findings is that, when tested in purely unimodal conditions, voice-identity processing appears normal in most cases of developmental prosopagnosia, as does face-identity processing in developmental phonagnosia. However, there is now first evidence that the multisensory nature of person identity impacts on identity recognition abilities in these cohorts. For example, unlike neurotypicals, auditory-only voice recognition is not enhanced in developmental prosopagnosia for voices which have been previously learned together with a face. This might also explain why the recognition of personally familiar voices is poorer in developmental prosopagnosics, compared to controls. In contrast, there is evidence that multisensory interactions might also lead to compensatory mechanisms in these disorders. For example, in developmental phonagnosia, voice recognition may be enhanced if voices have been learned with a corresponding face. Taken together, the reviewed findings challenge traditional models of person recognition which have assumed independence between face-identity and voice-identity processing and rather support an audio-visual model of human communication that assumes direction interactions between voice and face processing streams. In addition, the reviewed findings open up novel empirical research questions and have important implications for potential training regimes for developmental prosopagnosia and phonagnosia.

Improving Students Listening Ability Through Application Of Audio-Visual At Smpn 2 Painan

In order to learn a lesson well, we need to hear, see, ask questions about it, and discuss it with others. Not only that, teachers need to "do", which describe something in their own way, showing for example, tried to practice skills and tasks that require p What Knowledge they have earned. Problems to be studied in this research are: (1) pakah using Audio-Visual models in class IX students of SMP Negeri 2 Painan years 2015-2016? (2) angkah - steps involved in using the method of applying the Audio-Visual? Knowing that trigger low activity of learning and learning achievement exist on factors such as the method used by the teacher, so that the use or replacement of conventional methods into methods that are constructivist indispensable, consequently researchers tried learning model Audio-Visual in an attempt to solve Problems that exist in school. The low activity of learning and student achievement were presented at the background of the problem, the use of Audio-Visual learning model strived to be able to complete the purpose of this study is to determine the improvement of student achievement. How much improvement has been made clear at the end of the analysis. From the results of the research presented in Chapter IV and all the data that have been submitted, the research objectives submitted can already be achieved. To answer the research objectives namely the achievement of the increase in student learning achievement can be seen the evidence already disampaikan. From preliminary data nearly all students scored at the bottom, then the first cycle decreased to 8 students and second cycle the value of all the students on the school specified standards . From the initial average 4.5 rose to 6.3 in the first cycle and the second cycle increased to 7.9. From the preliminary data there are no students who completed while the first cycle to more that four students and the second cycle all students achieve mastery. Of all supporting data proving the achievement of learning objectives could be said that the model Audio-Visual can give the expected answer to the purpose of this research. All this can be achieved is due to the readiness and hard work of researchers from the start of the proposal, review the things that have not been good with my friends teachers, preparation of grids and research instruments, the use of means of data triangulation to the implementation of the maximum research.

Cross database audio visual speech adaptation for phonetic spoken term detection

Spoken term detection (STD), the process of finding all occurrences of a specified search term in a large amount of speech segments, has many applications in multimedia search and retrieval of information. It is known that use of video information in the form of lip movements can improve the performance of STD in the presence of audio noise. However, research in this direction has been hampered by the unavailability of large annotated audio visual databases for development. We propose a novel approach to develop audio visual spoken term detection when only a small (low resource) audio visual database is available for development. First, cross database training is proposed as a novel framework using the fused hidden Markov modeling (HMM) technique, which is used to train an audio model using extensive large and publicly available audio databases; then it is adapted to the visual data of the given audio visual database. This approach is shown to perform better than standard HMM joint-training method and also improves the performance of spoken term detection when used in the indexing stage. In another attempt, the external audio models are first adapted to the audio data of the given audio visual database and then they are adapted to the visual data. This approach also improves both phone recognition and spoken term detection accuracy. Finally, the cross database training technique is used as HMM initialization, and an extra parameter re-estimation step is applied on the initialized models using Baum Welch technique. The proposed approaches for audio visual model training have allowed for benefiting from both large extensive out of domain audio databases that are available and the small audio visual database that is given for development to create more accurate audio-visual models.

The Digital Turn in the French Audiovisual Model

En este artículo se aborda el cambio digital que se ha producido en el modelo audiovisual francés. El sistema organizativo y legal ha evolucionado con los cambios tecnológicos y las fuerzas económicas en los últimos treinta años. La industria de la televisión de altos ingresos sirvió como el elemento clave durante la década de 1980 para compensar el proceso de cambio de valor económico de las salas de cine a las pantallas domésticas y a los dispositivos personales. Sin embargo, la creciente competencia en el sector de la televisión y el auge de las empresas de tecnología han comenzado un proceso disruptivo. El desafío a la concepción francesa del derecho de autor, la débil posición de los canales de TV y el escalado de mercado de los contenidos ponen en tela de juicio la sostenibilidad del modelo francés en la era digital.

Gibraltar: la disputa por el espacio radioeléctrico de TV

In 1961 the conflict of Gibraltar between Spain and Britain affect the question of the broadcast television spectrum. Since 1960, Gibraltar Television is invading Spanish territory with its signal and the Franco's regime wants to eliminate this possibility of free press. With unpublished documents from the Archive of the Ministry of Foreign Affairs, the article explains the resolution of the conflict and its impact on current audiovisual model in the territory of Gibraltar.

Audio visual speech source separation via improved context dependent association model

In this paper, we exploit the non-linear relation between a speech source and its associated lip video as a source of extra information to propose an improved audio-visual speech source separation (AVSS) algorithm. The audio-visual association is modeled using a neural associator which estimates the visual lip parameters from a temporal context of acoustic observation frames. We define an objective function based on mean square error (MSE) measure between estimated and target visual parameters. This function is minimized for estimation of the de-mixing vector/filters to separate the relevant source from linear instantaneous or time-domain convolutive mixtures. We have also proposed a hybrid criterion which uses AV coherency together with kurtosis as a non-Gaussianity measure. Experimental results are presented and compared in terms of visually relevant speech detection accuracy and output signal-to-interference ratio (SIR) of source separation. The suggested audio-visual model significantly improves relevant speech classification accuracy compared to existing GMM-based model and the proposed AVSS algorithm improves the speech separation quality compared to reference ICA- and AVSS-based methods.

Joint Audiovisual Hidden Semi-Markov Model-Based Speech Synthesis

This paper investigates joint speaker-dependent audiovisual Hidden Semi-Markov Models (HSMM) where the visual models produce a sequence of 3D motion tracking data that is used to animate a talking head and the acoustic models are used for speech synthesis. Different acoustic, visual, and joint audiovisual models for four different Austrian German speakers were trained and we show that the joint models perform better compared to other approaches in terms of synchronization quality of the synthesized visual speech. In addition, a detailed analysis of the acoustic and visual alignment is provided for the different models. Importantly, the joint audiovisual modeling does not decrease the acoustic synthetic speech quality compared to acoustic-only modeling so that there is a clear advantage in the common duration model of the joint audiovisual modeling approach that is used for synchronizing acoustic and visual parameter sequences. Finally, it provides a model that integrates the visual and acoustic speech dynamics.

A comprehensive system for facial animation of generic 3D head models driven by speech

A comprehensive system for facial animation of generic 3D head models driven by speech is presented in this article. In the training stage, audio-visual information is extracted from audio-visual training data, and then used to compute the parameters of a single joint audio-visual hidden Markov model (AV-HMM). In contrast to most of the methods in the literature, the proposed approach does not require segmentation/classification processing stages of the audio-visual data, avoiding the error propagation related to these procedures. The trained AV-HMM provides a compact representation of the audio-visual data, without the need of phoneme (word) segmentation, which makes it adaptable to different languages. Visual features are estimated from the speech signal based on the inversion of the AV-HMM. The estimated visual speech features are used to animate a simple face model. The animation of a more complex head model is then obtained by automatically mapping the deformation of the simple model to it, using a small number of control points for the interpolation. The proposed algorithm allows the animation of 3D head models of arbitrary complexity through a simple setup procedure. The resulting animation is evaluated in terms of intelligibility of visual speech through perceptual tests, showing a promising performance. The computational complexity of the proposed system is analyzed, showing the feasibility of its real-time implementation.

Generating Human-Like Behaviors Using Joint, Speech-Driven Models for Conversational Agents

During human communication, every spoken message is intrinsically modulated within different verbal and nonverbal cues that are externalized through various aspects of speech and facial gestures. These communication channels are strongly interrelated, which suggests that generating human-like behavior requires a careful study of their relationship. Neglecting the mutual influence of different communicative channels in the modeling of natural behavior for a conversational agent may result in unrealistic behaviors that can affect the intended visual perception of the animation. This relationship exists both between audiovisual information and within different visual aspects. This paper explores the idea of using joint models to preserve the coupling not only between speech and facial expression, but also within facial gestures. As a case study, the paper focuses on building a speech-driven facial animation framework to generate natural head and eyebrow motions. We propose three dynamic Bayesian networks (DBNs), which make different assumptions about the coupling between speech, eyebrow and head motion. Synthesized animations are produced based on the MPEG-4 facial animation standard, using the audiovisual IEMOCAP database. The experimental results based on perceptual evaluations reveal that the proposed joint models (speech/eyebrow/head) outperform audiovisual models that are separately trained (speech/head and speech/eyebrow).

Audio-Visual Tibetan Speech Recognition Based on a Deep Dynamic Bayesian Network for Natural Human Robot Interaction

Audio-visual speech recognition is a natural and robust approach to improving human-robot interaction in noisy environments. Although multi-stream Dynamic Bayesian Network and coupled HMM are widely used for audio-visual speech recognition, they fail to learn the shared features between modalities and ignore the dependency of features among the frames within each discrete state. In this paper, we propose a Deep Dynamic Bayesian Network (DDBN) to perform unsupervised extraction of spatial-temporal multimodal features from Tibetan audio-visual speech data and build an accurate audio-visual speech recognition model under a no frame-independency assumption. The experiment results on Tibetan speech data from some real-world environments showed the proposed DDBN outperforms the state-of-art methods in word recognition accuracy.

Audio-visual speaker identification with asynchronous articulatory feature

A visual component is considerably supplementary to audio information and the apparent asynchrony between acoustic and visual cues may be effectively represented by an asynchronous articulatory feature. A new approach to speaker identification using an articulatory feature-based audio-visual model based on the dynamic Bayesian network is presented. Considerably satisfactory results were achieved in experiments on the audio-visual bimodal CMU database.

Automatic creation and evaluation of MPEG-7 compliant summary descriptions for generic audiovisual content

Today's world is characterized by the increasing availability of audiovisual content, created in many application domains and, thus, with rather different semantic characteristics. Audiovisual content is easily acquired, produced, processed, coded, stored and distributed, progressively making more important the ability for users to selectively consume the large amounts of content available. Automatic audiovisual summarization is a technology playing a major role towards facilitating the user's effective consumption of large amounts of audiovisual data in a reduced amount of time as time is getting more and more precious and scarce. This paper proposes an automatic summarization system for generic audiovisual content based on MPEG-7 compliant summary descriptions. To evaluate the quality of the created summaries, a user evaluation methodology was designed, and applied with promising results, showing that the developed application is able to summarize with success generic audiovisual content, especially high action content. The main novelty of this paper is related to the usage of the MPEG-7 summarization tools in combination with an arousal-based audiovisual summarization model, and to the novel user evaluation methodology and study.

Importance of Facial Physical Attractiveness of Audiovisual Models in Descriptions and Preferences of Children and Adolescents

We performed a cross-sectional study with three age groups (8, 14, and 17 years) to evaluate developmental differences in stereotyped beliefs about physical attractiveness and the value of this as perceived by the participants. Given the current importance of television in the development of social knowledge, television models were used. The children and adolescents were asked to evaluate, using bipolar open scales, the physical attractiveness, likeableness, generosity, intelligence, fun, and altruism of 12 television models of both sexes, previously selected by judges, as well as the desire to resemble or feel close to the models. Analysis showed developmental differences across age groups both in the concept of physical attractiveness and in stereotyped beliefs about this. As in other areas of social knowledge, the younger children's responses were bipolar, global, and much more stereotyped, while the adolescents introduced subtle distinctions and elaborated their responses. Nevertheless, physical attractiveness appeared a desirable characteristic for all age groups.