Voice Parameter Analysis for the disease detection
The analysis of the human voice has arisen as an important area of study for its various applications in medical as well as engineering sciences. Voice analysis basically deals with extraction of some parameters from voice signal for processing of voice in desirable applicability by using suitable techniques. This paper states the certain common medical conditions which affect voice patterns of patients in evidence to leading research studies that had verified the voice alterations as diagnosis symptom in respective medical conditions. As well as, a comparative study of voice analysis techniques will be presented and special emphasis is given to certain prominent biomedical tools that are commercially available and are fundamentally based on voice analysis technology. Recent advancements in the field of voice analysis systems are also given.
To integrate CA systems with other applications in the CIM world one principal approach currently under development is the feature recognition pro cess based on graph grammars It enables any CIM component to recognize the higher level entities the so called features used in this component out of a lower data exchange format which might be the internal representation of a CAD system as well as some standard data exchange format In this pa per we present a made to measure parsing algorithm for feature recognition The heuristic driven chart based bottom up parser analyzes attributed node labeled graphs representing workpieces with a feature speci c attributed node labeled graph grammar representing the feature de nitions yielding a high level qualitative description of the workpiece in terms of features