Hidden Markov Models

Hidden Markov Models (HMMs), although known for decades, have made a big career nowadays and are still in state of development. This book presents theoretical issues and a variety of HMMs applications in speech recognition and synthesis, medicine, neurosciences, computational biology, bioinformatics, seismology, environment protection and engineering. I hope that the reader will find this book useful and helpful for their own research

Towards speech recognition using palato-lingual contact patterns for voice restoration.

The loss of speech following a laryngectomy presents substantial challenges, and a number of devices have been developed to assist these patients. These devices range from the electrolarynx to tracheoesophageal speech. However, all of these devices and techniques have concentrated on producing sound from the patient’s vocal tract. Research into a new type of artificial larynx is presented. This new device utilizes the measurement of dynamic tongue-palate contact patterns to infer intended speech. The dynamic tongue measurement is achieved with the use of an existing palatome- ter and pseudopalate. These signals are then converted to 2-D Space-Time plots and feature extraction methods (such as Principal Component Analysis, Fourier Descrip- tors and Generic Fourier Descriptors) are used to extract suitable features for use as input to neural network systems. Two types of neural network (Multi-layer Percep- trons and Support Vector Machines) are investigated and a voting system is formed. The final system can correctly identify fifty common English words 94.14% of the time with a rejection rate of 17.74%. Voice morphing is investigated as a technique to match the artificially synthesized voice to the laryngectomy patient’s original voice. It is successfully implemented thus creating a transfer function that can change one person’s voice to sound like another’s. Once the voting system has correctly identified the word said by the patient the word is then synthesized in the patient’s pre-laryngectomy voice. The final artificial larynx system solves a number of the problems inherent in previ- ous artificial larynx designs (such as poor voice quality and invasiveness). This new artificial larynx uses current technology in a new way to produce a viable solution for alaryngeal patients

Mathematics and Digital Signal Processing

Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems

Chapter From the Lab to the Real World: Affect Recognition Using Multiple Cues and Modalities

Interdisciplinary concept of dissipative soliton is unfolded in connection with ultrafast fibre lasers. The different mode-locking techniques as well as experimental realizations of dissipative soliton fibre lasers are surveyed briefly with an emphasis on their energy scalability. Basic topics of the dissipative soliton theory are elucidated in connection with concepts of energy scalability and stability. It is shown that the parametric space of dissipative soliton has reduced dimension and comparatively simple structure that simplifies the analysis and optimization of ultrafast fibre lasers. The main destabilization scenarios are described and the limits of energy scalability are connected with impact of optical turbulence and stimulated Raman scattering. The fast and slow dynamics of vector dissipative solitons are exposed