الصفحة 1
الصفحة 1
New advances in audio signal processing
In the era of digitalization, audio signal processing is gaining peculiar relevance as an automation and remote analysis means, also considering its enhancement by novel artificial intelligence (AI) techniques. This Reprint aims to offer an overview of the current developments in all fields that revolve around audio processing: from advancements in the acoustic domain to deep learning architectures for the audio-based analysis of real-world problems such as pitch detection or pathology identification.
Modal Array Signal Processing : Principles and Applications of Acoustic Wavefield Decomposition
Many applications of acoustic signal processing, such as teleconferencing and surveillance systems, require an estimate of several parameters present in the observed acoustic wavefield. The most important parameters are the number as well as the location of active acoustic sources. This book deals with the problem of detecting and localizing multiple simultaneously active wideband acoustic sources by applying the notion of wavefield decomposition using circular and spherical microphone arrays. The decomposed wavefield representation is used to serve as a basis for so-called modal array signal processing algorithms, which have the significant advantage over classical array signal processing algorithms that they inherently support multiple wideband acoustic sources. A rigorous derivation of modal array signal processing algorithms for unambiguous source detection and localization as well as performance evaluations by means of measurements using an actual real-time capable implementation are discussed.
Microphone Array Signal Processing
Microphone arrays have attracted a lot of interest in the last two decades. The reason behind this is that they have the potential to solve many important problems in both human-machine and human-human interfaces for different kinds of communications. But before microphone arrays can be deployed broadly, there is a strong need for a deep understanding of the problems encountered in the real world and their clear formulation in order that useful algorithms can be developed to process the sensor signals.
Crime detection camera
This paper presents a comprehensive crime detection system that uses a combination of hardware and software to monitor homes and communities in real time. The system consists of a Raspberry Pi 4B, a Raspberry Pi Camera V2, a flame sensor, an MQ-6 gas sensor, and a microphone, which are all connected to a database management system powered by MySQL. The data collected from these devices is analyzed by machine learning algorithms to detect crimes, such as theft or robbery, as well as fires and gas leaks. The system also includes a mobile app, ‘Safe Home’ which provides live video monitoring and real-time notifications to users, and an employee dashboard to monitor all statistics and manage all implemented systems.
Creating Web-based Laboratories
Remote web-based experimentation, enabling students and researchers to access the laboratory anytime via the Internet, is becoming an increasingly attractive way to complement or even replace traditional laboratory sessions. Placing a video camera & microphone before the equipment and apparatus to capture what is actually happening in the laboratory allows the images and audio data to be streamed to the client side. Researchers in different countries can share equipment and conduct research cooperatively and remotely. The authors summarise their research and discuss the development of the 5 web-based laboratories launched from the National University of Singapore. The principles, structure, and technologies required for the creation of Internet remote experimentation systems are discussed with particular emphasis on the integration of hardware and software systems. Also highlighted is the design and development of interfaces and components for use in typical web-based laboratories or similar web-control applications.
Blind Speech Separation
This is the first book to provide a cutting edge reference to the fascinating topic of blind source separation (BSS) for convolved speech mixtures. Through contributions by the foremost experts on the subject, the book provides an up-to-date account of research findings, explains the underlying theory, and discusses potential applications. The individual chapters are designed to be tutorial in nature with specific emphasis on an in-depth treatment of state of the art techniques. Blind Speech Separation is divided into three parts:Part 1 presents overdetermined or critically determined BSS. Here the main technology is independent component analysis (ICA). ICA is a statistical method for extracting mutually independent sources from their mixtures. Part 2 addresses underdetermined BSS, where there are fewer microphones than source signals. Here, the sparseness of speech sources is very useful; we can utilize time-frequency diversity, where sources are active in different regions of the time-frequency plane.Part 3 presents monaural BSS where there is only one microphone. Here, we can separate a mixture by using the harmonicity and temporal structure of the sources. We can build a probabilistic framework by assuming a source model, and separate a mixture by maximizing the a posteriori probability of the sources.
Acoustic MIMO Signal Processing
Telecommunication systems and human-machine interfaces start employing multiple microphones and loudspeakers in order to make conversations and interactions more lifelike, hence more efficient. This development gives rise to a variety of acoustic signal processing problems under multiple-input multiple-output (MIMO) scenarios, encompassing distant speech acquisition, sound source localization and tracking, echo and noise control, source separation and speech dereverberation, and many others. The last decade has witnessed a growing interest in exploring these problems, but there has been little effort to develop a theory to have all these problems investigated in a unified framework. This unique book attempts to fill the gap.
