Springer, 2005. — 319 p.Over the past thirty years, much progress has been made in the field of automatic speech recognition (ASR). Research has progressed from basic recognition tasks involving digit strings in clean environments to more demanding and complex tasks involving large vocabulary continuous speech recognition. Yet, limits exist in the ability of these speech recognition systems to perform in real-world settings. Factors such as environmental noise, changes in acoustic or microphone conditions, variation in speaker and speaking style all significantly impact speech recognition performance for today systems. Yet, while speech recognition algorithm development has progressed, so has the need to transition these working platforms to realworld applications. It is expected that ASR will dominate the humancomputer interface for the next generation in ubiquitous computing and information access. Mobile devices such as PDAs and cellular telephones are rapidly morphing into handheld communicators that provide universal access to information sources on the web, as well as supporting voice, image, and video communications. Voice and information portals on the WWW are rapidly expanding, and the need to provide user access to larger amounts of audio, speech, text, and image information is ever expanding. The vehicle represents one significant emerging domain where information access and integration is rapidly advancing. This textbook is focused on digital signal processing strategies for improving information access, command and control, and communications for in-vehicle environments. It is expected that the next generation of human-to-vehicle interfaces will incorporate speech, video/image, and wireless communication modalities to provide more efficient and safe operations within car environments. It is also expected that vehicles will become smart and provide a level of wireless information sharing of resources regarding road, weather, traffic, and other information that drivers may need immediately or request at a later time while driving on the road. It is also important to note that while human interface technology continues to evolve and expand, the demands placed on the vehicle operator must also be kept in mind to minimize task demands and increase safety. The motivation for this textbook evolved from many high quality papers that were presented at the DSP in Mobile and Vehicular Systems Workshop, Nagoya, Japan, April 2003, with generous support from CIAIR, Nagoya University. From that workshop, a number of presentations were selected to be expanded for this textbook. The format of the textbook is centered about three themes: (i) in-vehicle corpora, (ii) speech recognition/dialog systems with emphasis on car environments, and (iii) DSP for mobile platforms involving noise suppression, image/video processing, and alternative communication scenarios that can be employed for in-vehicle applications.Construction and Analysis of a Multi-layered In-car Spoken Dialogue Corpus CU-Move: Advanced In-Vehicle Speech Systems for Route Navigation A Spoken Dialog Corpus for Car Telematics Services Experiences of Multi-speaker Dialogue System for Vehicular Information Retrieval Robust Dialog Management Architecture using VoiceXML for Car Telematics Systems Use of Multiple Speech Recognition Units in an In-car Assistance System Hi-speed Error Correcting Code LSI for Mobile Phone MCMAC as an Amplitude Spectral Estimator for Speech Enhancement Noise Robust Speech Recognition using Prosodic Information Reduction of Diffuse Noise in Mobile and Vehicular Applications. Speech Enhancement based on F-Norm Constrained Truncated SVD Algorithm Verbkey - A Single-Chip Speech Control for the Automobile Environment Real-time Transmission of H.264 Video over 802.11B-based Wireless ad hoc Networks DWT Image Compression for Mobile Communication Link-adaptive Variable Bit-rate Speech Transmission over 802.11 Wireless LANs Joint Audio-Video Processing for Robust Biometric Speaker Identification in Car Is Our Driving Behavior Unique? Robust ASR Inside A Vehicle Using Blind Probabilistic Based Under-determined Convolutive Mixture Separation Technique In-car Speech Recognition using Distributed Microphones
Чтобы скачать этот файл зарегистрируйтесь и/или войдите на сайт используя форму сверху.