This book provides a cross-disciplinary reference to speech in mobile and pervasive environments Speech in Mobile and Pervasive Environments addresses the issues related to speech processing on resource-constrained mobile devices. These include speech recognition in noisy environments, specialised hardware for speech recognition and synthesis, the use of context to enhance recognition and user experience, and the emerging software standards required for interoperability. This book takes a multi-disciplinary look at these matters, while offering an insight into the opportunities and challenges of speech processing in mobile environs. In developing regions, speech-on-mobile is set to play a momentous role, socially and economically; the authors discuss how voice-based solutions and applications offer a compelling and natural solution in this setting. Key Features Provides a holistic overview of all speech technology related topics in the context of mobility Brings together the latest research in a logically connected way in a single volume Covers hardware, embedded recognition and synthesis, distributed speech recognition, software technologies, contextual interfaces Discusses multimodal dialogue systems and their evaluation Introduces speech in mobile and pervasive environments for developing regions This book provides a comprehensive overview for beginners and experts alike. It can be used as a textbook for advanced undergraduate and postgraduate students in electrical engineering and computer science. Students, practitioners or researchers in the areas of mobile computing, speech processing, voice applications, human-computer interfaces, and information and communication technologies will also find this reference insightful. For experts in the above domains, this book complements their strengths. In addition, the book will serve as a guide to practitioners working in telecom-related industries.
Pervasive Computing integrates numerous, casually accessible and inexpensive mobile devices with traditional distributed systems. The foremost issue of pervasive computing is Context-Awareness. Context-awareness requires flexible context sensing and context interpretation mechanism that are used in smart service discovery and its subsequent delivery to the mobile user. The proposed research, CAPP, is a Service Oriented Architecture (SOA) that enhances smart service discovery in a pervasive environment. Objective of CAPP is to deliver the best service available, among a pool of similar services, to the user. The interpreted high-level context is then used to discover the best available service for the user. The proposed system is implemented in Java and simulated through test data. Results show that the proposed technique is promising.
Construction researchers and industry practitioners have begun to explore the possibilities offered by mobile and pervasive computing in architecture, engineering and construction (AEC). It is expected that the construction industry will be keen to apply these technologies as they promise significant benefits in areas such as materials management, project management, distributed collaboration and information management, all leading to improvements in productivity. This book offers a comprehensive reference volume to the use of mobile and pervasive computing in construction. Based on contributions from a mix of leading researchers and experts from academia and industry, it provides up-to-date insights into current research topics in this field as well as the latest technological advancements and practical examples. The chapters introduce the key theoretical concepts in mobile and pervasive computing and highlight the applications and solutions which are available to the construction industry. More specifically, the book focuses on the manner in which these technologies can be applied to improve practices in construction and related industries. This book will be of particular interest to academics, researchers, and graduate students at universities and industrial practitioners seeking to apply mobile and pervasive computing systems to improve construction industry productivity.
With the recent advances in speech signal processing techniques, the need to detect the presence of speech accurately in the incoming signal under different noise environments has become a major concern of the industry. The separation of speech segment from the non-speech segment in an audio signal is achieved using a Voice Activity Detectors (VAD). VAD’s are a class signal processing methods that detects the presence or absence of speech in short segments of audio signal. A VAD has a pivotal role as a preprocessing block in wide range of speech applications. An integrated VAD in speech communication system, improves channel capacity, reduces co-channel interference and power consumption in portable electronic devices in cellular radio systems and allows simultaneous voice and data applications in multimedia communications. In slowly varying non-stationary environments where speech is corrupted by noise, a VAD is used to learn noise characteristics and estimate the noise spectrum. Furthermore, the output from the VAD is helpful in improving the performance of the speech recognition systems which applies a technique called non-speech frame dropping (FD) to reduce the insertion error
The accessibility of mobile terminals, which tend to be lighter and smaller, hampers the development of new services over wireless networks. This trend makes it more difficult, or even frustrates, the interaction of the user with the service. Thus, the development of new user interfaces, providing a ubiquitous, pervasive and multimodal interaction, is a necessary step for the next generation of mobile services. In this scene, automatic speech recognition is a promising way for an easy and natural user access to network services. However, mobile devices are characterized by a restricted computing power, small limited-speed memories and short battery life. In this work, we show how speech recognition based on VoIP technologies allows circumventing these hardware constraints by moving the most complex computational tasks of speech recognition to a remote server. Under this approximation, the user device has to send coded speech or speech parameters through IP networks, which were not designed for real-time communications. For this reason, special emphasis is placed on proposing efficient techniques to avoid the negative impact of network impairments on speech recognition performance.
This book encapsulates the rich texture of Rajput women’s life in Chambi, a small village in Himachal Pradesh. It represents the various roles of Rajput women in family, marriage, politics, economy and religion through an intensive field work study. It also highlights the transitional phase of Rajput women and the associated shift in their roles. This book stressed the inter-relatedness of various sub-systems of the social structure.This book will be useful to young scholars and researchers working in the field of gender studies.
Present day research is mainly focused on speech enhancement in mobiles, laptops , every electronic goods. In which spatial filleting using microphone array beamformining is popular one. So myself and my professor Nedelko grabic Has started research on this branch. we have designed a SRP-PHAT source-localization and an optimal beamformer which extracted the speech optimally in reverberant and noise environments.
For future generation distributed systems to be truly pervasive, they must incorporate, ideally, every networked service and resource. With the notion of resource constantly shifting from the raw computational resources of the early days of high- performance oriented systems, to any type of capability in modern mobile and pervasive systems, we take a fresh look at the intersection of distributed computing systems (and more specifically the Grid) and mobile computing. The latter, we argue in this thesis, can contribute significant functionality and extend the applicability of the Grid, in the context of a fully integrated system. To this end, we introduce the Virtual Cluster architecture and Dynamic Service Aggregation, to provide a high-level virtualized view of the mobile domain. The series of experiments and use cases discussed, illustrate the potential applicability, before we set the tone for future developments in fully integrated mobile Grid environments.
This book focuses on automatic speech recognition in clean and noisy or reverbrant environments. Therefore, a parallel speech recognition system using TempoRAL Patterns (TRAPs) is described. The TRAPs are computed over a rather long temporal context for each critical band in the signal's spectrum. Then, the features of the different bands are combined. Thus recognition only in certain bands is possible. This is beneficial if noise only occurs in parts of the spectrum. In this manner multiple speech recognizers are trained which analyze disjoint parts of the frequency domain. Each of the speech recognizers extracts a different word chain from the audio signal. In the end the word chains are merged to form a single recognition result. As shown on different data sets the parallel speech recognition system is much more robust to noise and reverberation than the state-of-the-art baseline system.
Recent days, speech quality is one of the most important factors in mobile communication and the quality depends on Signal-to-Noise Ratio (SNR) improvement. Dual Microphone System (DMS) can recover a speech from noisy environment with the help of different algorithms. This paper contributes to reduce babble speech noise by developing the dual microphone system with two Omni-directional microphones for close talk handset mode in mobile phone. It can also find out the position of microphones in a mobile. This system is successfully compressed the babble noise and improve the quality of speech.
Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal processing, pattern recognition, machine learning and artificial intelligence. SLU systems are designed to extract the meaning from speech utterances and its applications are vast, from voice search in mobile devices to meeting summarization, attracting interest from both commercial and academic sectors. Both human/machine and human/human communications can benefit from the application of SLU, using differing tasks and approaches to better understand and utilize such communications. This book covers the state-of-the-art approaches for the most popular SLU tasks with chapters written by well-known researchers in the respective fields. Key features include: Presents a fully integrated view of the two distinct disciplines of speech processing and language processing for SLU tasks. Defines what is possible today for SLU as an enabling technology for enterprise (e.g., customer care centers or company meetings), and consumer (e.g., entertainment, mobile, car, robot, or smart environments) applications and outlines the key research areas. Provides a unique source of distilled information on methods for computer modeling of semantic information in human/machine and human/human conversations. This book can be successfully used for graduate courses in electronics engineering, computer science or computational linguistics. Moreover, technologists interested in processing spoken communications will find it a useful source of collated information of the topic drawn from the two distinct disciplines of speech processing and language processing under the new area of SLU.
Book Statement: A microphone array is the promising solution for realizing hands-free speech recognition in real environments. Accurate talker localization is very important for speech recognition using the microphone array. However localization of a moving talker is difficult in noisy reverberant environments. The talker localization errors degrade the performance of speech recognition. A speech recognition algorithm is implemented to solve the problem, which considers multiple talker direction hypotheses. Abstract: This book describes the design and implementation of a speech enhancement system that uses 4-channel microphone array beam forming and speech enhancement algorithms applied to a speech signal in a multiple source environment. To locate the accurate Direction of Arrival (DOA) from the source, it is necessary to design a suitable microphone array system with more efficient localization algorithm. The goal of the system is to improve the quality of the primary speech signal. The target groups for which the book was written are Room Impulse Response (RIR), Reverberation, WOLA Filter Bank, Adaptive Beamformers, SRP-PHAT.
Normally speech signals are contaminated with noise and interference that reduces the intelligibility of speech during communication. In order to make speech signals effective and useful, they need to be enhanced from the noisy speech signal. In speech processing field many speech enhancement techniques are developed and are providing very good results. Multichannel microphone array is also one of the techniques used for speech enhancement, that provides better results than the single channel speech enhancement. Moreover, Wiener filtering is the most commonly used technique for multichannel microphone array for speech enhancement. The main focus of this thesis is to implement multichannel microphone array using Wiener filtering in the modulation domain system and also in the time domain system to enhance the speech.
This lecture presents a first compendium of established and emerging standards in pervasive computing systems. The lecture explains the role of each of the covered standards and explains the relationship and interplay among them. Hopefully, the lecture will help piece together the various standards into a sensible and clear landscape. The lecture is a digest, reorganization, and a compilation of several short articles that have been published in the "Standards and Emerging Technologies" department of the IEEE Pervasive Computing magazine. The articles have been edited and shortened or expanded to provide the necessary focus and uniform coverage depth. There are more standards and common practices in pervasive systems than the lecture could cover. However, systems perspective and programmability of pervasive spaces, which are the main foci of the lecture, set the scope and determined which standards should be included. The lecture explains what it means to program a pervasive space and introduces the new requirements brought about by pervasive computing. Among the standards the lecture covers are sensors and device standards, service-oriented device standards, service discovery and delivery standards, service gateway standards, and standards for universal interactions with pervasive spaces. In addition, the emerging sensor platform and domestic robots technologies are covered and their essential new roles explained. The lecture also briefly covers a set of standards that repre...
Mobile computing research is expanding beyond the traditional approach on voice and data delivery to encompass new classes of rich mobile applications such as location based services, mobile social networks, crowd computing and sensory based applications. These classes of mobile applications have quantitative and qualitative criteria of growing importance like efficiency and performance, scalability, privacy and reliability. The next generation of mobile enterprise systems will monitor and analyze the mobile computing ecosystem and adapt their execution environments and resources accordingly. In this work I focus on orchestrating all components of such a complex system to have an optimal mobile cloud computing enterprise which meets users and providers' concerns.