Speech Processing Research Program

Contains an introduction and reports on five research projects.National Science Foundation Grant MIP 87-14969National Science Foundation FellowshipU.S. Air Force - Electronic Systems Division Contract F1 9628-89-K-0041U.S. Navy - Office of Naval Research Contract N00014-89-J-148

Speech Processing Research Program

Contains an introduction and reports on five research projects.National Science Foundation FellowshipNational Science Foundation Grant MIP 87-14969U.S. Navy - Office of Naval Research Contract N00014-89-J-1489U.S. Air Force - Electronic Systems Division Contract F19628-89-K-0041National Science Foundation Fellowshi

Advanced Television and Signal Processing Program

Contains an introduction and reports on fifteen research projects.Advanced Television Research ProgramAdams-Russell Electronics, Inc.National Science Foundation Fellowship Grant MIP 87-14969National Science Foundation FellowshipU.S. Navy - Office of Naval Research Grant N00014-89-J-1489U.S. Air Force - Electronic Systems Division Contract F1 9628-89-K-004

Digital Signal Processing

Contains table of contents for Part III, table of contents for Section 1, an introduction and reports on seventeen research projects.National Science Foundation FellowshipNational Science Foundation (Grant ECS 84-07285)National Science Foundation (Grant MIP 87-14969)U.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)Scholarship from the Federative Republic of BrazilU.S. Air Force - Electronic Systems Division (Contract F19628-85-K-0028)AT&T Bell Laboratories Doctoral Support ProgramCanada, Bell Northern Research ScholarshipCanada, Fonds pour la Formation de Chercheurs et I'Aide a la Recherche Postgraduate FellowshipSanders Associates, Inc.OKI Semiconductor, Inc.Tel Aviv University, Department of Electronic SystemsU.S. Navy - Office of Naval Research (Contract N00014-85-K-0272)Natural Sciences and Engineering Research Council of Canada, Science and Engineering Scholarshi

An Event-Based Method For Microphone Array Speech Enhancement

This paper presents the Multi-Channel Multi-Pulse (MCMP) algorithm for the enhancement of speech degraded by reverberations and additive noise. The enhanced speech is synthesized from a sequence of impulses exciting a linear predictive filter. The excitation signal is computed from a nonlinear process which uses impulse clustering of the multi-channel speech data to discriminate portions of the linear prediction residual produced by the desired speech signal from those due to multipath effects and uncorrelated noise. The MCMP algorithm is shown to be capable of identifying and attenuating reverberant portions of the speech signal as well as reducing the effects of additive noise. 1. INTRODUCTION There is a direct relationship between the effectiveness, functionality, and ease of use of a human-computer interface and the capabilities of the speech acquisition system upon which it depends. Currently, most speech acquisition systems require the user to be close to a microphone if reasona..

A Pitch-Based Approach To Time-Delay Estimation Of Reverberant Speech

Generalized Cross-Correlation (GCC) has been the traditional method for estimating the relative time-delay associated with the speech signals received by a pair of microphones in a reverberant, noisy environment. The filtering criterion employed is either focussed on the signal degradations due to additive noise or those due exclusively to multipath channel effects. There has been relatively little success at applying GCC weighting schemes which are robust to both of these conditions. This paper details an alternative approach which attempts to employ a signal dependent criterion, namely the estimated periodicity of harmonic spectral intervals, to design a GCC filter appropriate for the combination of noise and multipath signal distortions. Simulations are performed across a range of room conditions to illustrate the utility of the proposed time-delay estimation method relative to conventional GCC filtering approaches. 1. INTRODUCTION The accurate estimation of the relative time dela..

Multi-Source Face Tracking With Audio And Visual Data

A real-time, face tracker based on both sound and visual cues is presented. Initial talker locations are estimated acoustically from microphone array data while precise localization and tracking are derived from visual data. The image processing employs a hierarchical structure which utilizes source motion, contour geometry, color data, and facial features. The resulting system is capable of tracking multiple people in complex backgrounds and robustly discriminating faces from similar objects. While the direct focus of this work is automated video conferencing, the face tracking capability has utility to manymultimedia and virtual reality applications

A Subset Approach to Contour Tracking in Clutter

A new method for tracking contours of moving objects in clutter is presented. For a given object, a model of its contours is learned from training data in the form of a subset of contour space. Greater complexity is added to the contour model by analyzing rigid and non-rigid transformations of contours separately. In the course of tracking, multiple contours may be observed due to the presence of extraneous edges in the form of clutter; the learned model guides the algorithm in picking out the correct one. The algorithm, which is posed as a solution to a minimization problem, is made efficient by the use of several iterative schemes. Results applying the proposed algorithm to the tracking of a flexing finger and to a conversing individual's lips are presented. 1. Problem Motivation and Review This work addresses the tracking of moving contours in a video-stream. Specifically, given a sequence of images in which a known object of interest is in motion, the goal is to track the object's..