Review of Research on Speech Technology: Main Contributions From Spanish Research Groups

In the last two decades, there has been an important increase in research on speech technology in Spain, mainly due to a higher level of funding from European, Spanish and local institutions and also due to a growing interest in these technologies for developing new services and applications. This paper provides a review of the main areas of speech technology addressed by research groups in Spain, their main contributions in the recent years and the main focus of interest these days. This description is classified in five main areas: audio processing including speech, speaker characterization, speech and language processing, text to speech conversion and spoken language applications. This paper also introduces the Spanish Network of Speech Technologies (RTTH. Red Temática en Tecnologías del Habla) as the research network that includes almost all the researchers working in this area, presenting some figures, its objectives and its main activities developed in the last years

USING DEEP LEARNING-BASED FRAMEWORK FOR CHILD SPEECH EMOTION RECOGNITION

Biological languages of the body through which human emotion can be detected abound including heart rate, facial expressions, movement of the eyelids and dilation of the eyes, body postures, skin conductance, and even the speech we make. Speech emotion recognition research started some three decades ago, and the popular Interspeech Emotion Challenge has helped to propagate this research area. However, most speech recognition research is focused on adults and there is very little research on child speech. This dissertation is a description of the development and evaluation of a child speech emotion recognition framework. The higher-level components of the framework are designed to sort and separate speech based on the speaker’s age, ensuring that focus is only on speeches made by children. The framework uses Baddeley’s Theory of Working Memory to model a Working Memory Recurrent Network that can process and recognize emotions from speech. Baddeley’s Theory of Working Memory offers one of the best explanations on how the human brain holds and manipulates temporary information which is very crucial in the development of neural networks that learns effectively. Experiments were designed and performed to provide answers to the research questions, evaluate the proposed framework, and benchmark the performance of the framework with other methods. Satisfactory results were obtained from the experiments and in many cases, our framework was able to outperform other popular approaches. This study has implications for various applications of child speech emotion recognition such as child abuse detection and child learning robots

Affective Computing in the Area of Autism

The prevalence rate of Autism Spectrum Disorders (ASD) is increasing at an alarming rate (1 in 68 children). With this increase comes the need of early diagnosis of ASD, timely intervention, and understanding the conditions that could be comorbid to ASD. Understanding co-morbid anxiety and its interaction with emotion comprehension and production in ASD is a growing and multifaceted area of research. Recognizing and producing contingent emotional expressions is a complex task, which is even more difficult for individuals with ASD. First, I investigate the arousal experienced by adolescents with ASD in a group therapy setting. In this study I identify the instances in which the physiological arousal is experienced by adolescents with ASD ( have-it ), see if the facial expressions of these adolescents indicate their arousal ( show-it ), and determine if the adolescents are self-aware of this arousal or not ( know-it ). In order to establish a relationship across these three components of emotion expression and recognition, a multi-modal approach for data collection is utilized. Machine learning techniques are used to determine whether still video images of facial expressions could be used to predict Electrodermal Activity (EDA) data. Implications for the understanding of emotion and social communication difficulties in ASD, as well as future targets for intervention, are discussed. Second, it is hypothesized that a well-designed intervention technique helps in the overall development of children with ASD by improving their level of functioning. I designed and validated a mobile-based intervention designed for teaching social skills to children with ASD. I also evaluated the social skill intervention. Last, I present the research goals behind an mHealth-based screening tool for early diagnosis of ASD in toddlers. The design purpose of this tool is to help people from low-income group, who have limited access to resources. This goal is achieved without burdening the physicians, their staff, and the insurance companies

Human-computer interaction in ubiquitous computing environments

Purpose &ndash; The purpose of this paper is to explore characteristics of human-computer interaction when the human body and its movements become input for interaction and interface control in pervasive computing settings. Design/methodology/approach &ndash; The paper quantifies the performance of human movement based on Fitt\u27s Law and discusses some of the human factors and technical considerations that arise in trying to use human body movements as an input medium. Findings &ndash; The paper finds that new interaction technologies utilising human movements may provide more flexible, naturalistic interfaces and support the ubiquitous or pervasive computing paradigm. Practical implications &ndash; In pervasive computing environments the challenge is to create intuitive and user-friendly interfaces. Application domains that may utilize human body movements as input are surveyed here and the paper addresses issues such as culture, privacy, security and ethics raised by movement of a user\u27s body-based interaction styles. Originality/value &ndash; The paper describes the utilization of human body movements as input for interaction and interface control in pervasive computing settings. <br /

Ambulatory assessment for physical activity research. State of the science, best practices and future directions

Technological and digital progress benefits physical activity (PA) research. Here we compiled expert knowledge on how Ambulatory Assessment (AA) is utilized to advance PA research, i.e., we present results of the 2nd International CAPA Workshop 2019 "Physical Activity Assessment - State of the Science, Best Practices, Future Directions" where invited researchers with experience in PA assessment, evaluation, technology and application participated. First, we provide readers with the state of the AA science, then we give best practice recommendations on how to measure PA via AA and shed light on methodological frontiers, and we furthermore discuss future directions. AA encompasses a class of methods that allows the study of PA and its behavioral, biological and physiological correlates as they unfold in everyday life. AA includes monitoring of movement (e.g., via accelerometry), physiological function (e.g., via mobile electrocardiogram), contextual information (e.g., via geolocation-tracking), and ecological momentary assessment (EMA; e.g., electronic diaries) to capture self-reported information. The strengths of AA are data assessment that near real-time, which minimizes retrospective biases in real-world settings, consequentially enabling ecological valid findings. Importantly, AA enables multiple assessments across time within subjects resulting in intensive longitudinal data (ILD), which allows unraveling within-person determinants of PA in everyday life. In this paper, we show how AA methods such as triggered e-diaries and geolocation-tracking can be used to measure PA and its correlates, and furthermore how these findings may translate into real-life interventions. In sum, AA provides numerous possibilities for PA research, especially the opportunity to tackle within-subject antecedents, concomitants, and consequences of PA as they unfold in everyday life. In-depth insights on determinants of PA could help us design and deliver impactful interventions in real-world contexts, thus enabling us to solve critical health issues in the 21st century such as insufficient PA and high levels of sedentary behavior. (DIPF/Orig.