Helmut Lagger

Knowledge based design flow management

The knowledge regarding design flow management is described and modeled by predicate-transition Petri nets and production rules. The approach offers a clear and flexible tool control mechanism within a CAD framework such that both static and dynamic behavior of a design flow are supported. The authors also demonstrate how different forms of knowledge can be implemented by a rule based system, OPS83, and be integrated in the HILDA CAD framework to guide the users through the design process.<<ETX>>

A coarse phonetic knowledge source for template independent large vocabulary word recognition

In this paper we present a template independent knowledge source (KS), that uses coarse phonetic information to substantially constrain the candidate vocabulary for use in word hypothesization with very large vocabularies. It consists of three parts: the segmenter that breaks a test utterance up into a sequence of coarse phonetic classes, the knowledge compiler that generates a reference dictionary containing the appropriate coarse phonetic representations for each word candidate and finally, a matching engine. Coarse phonetic classification is performed using linear discriminant analysis, more specifically perceptron classification. The knowledge compiler first generates a phonemic representation and segmental durations by rule from a list of word candidates (i.e., from text), and then derives coarse phonetic class segments. Matching is performed by a nonlinear time alignment algorithm based on dissimilarity scores between detected and lexical coarse class segments. The coarse phonetic KS was tested by compiling a word list of approximately 1500 words. Using only the coarse classes Silence, Plosive, Fricative, Vocalic, Front Vowel, Back Vowel, Nasal and R, a vocabulary reduction to 5% of the original vocabulary is achieved at lower than 5% error rate for three different speakers.

Large-vocabulary isolated word recognition with fast coarse time alignment

An isolated word recognition system for large vocabularies (1000 words and up) with an average recognition rate of more than 98 per cent is presented. Each utterance is characterized by a sequence of feature vectors which are obtained by an autocorrelation analysis. The resulting coefficients are quantized in such a way, that an entire feature vector can be stored in a single data word. A distance measure adapted to this representation has been developed. The classification is performed hierarchically in two steps. In the preselection stage, the words are divided into 16 segments and hardware is employed for a coarse nonlinear mapping. A short ranked list of candidates is processed by the following final classifier which performs a nonlinear time alignment of the fully resolved patterns using Dynamic Programming. Thus a short response time and a high recognition performance of the system are achieved. Without full use of parallelism an overall response time for the large vocabulary of less than one second is obtained on a signal processor.

Trapdoors in knapsack kryptosystems

A way to attack public-key cryptosystems based on the knapsack problem is proposed. The basic idea of the approach described is to find pairs of natural numbers, namely values for a modulus m and a multiplier w, which reduce the knapsack elements simultaneously by modular multiplication. The ratio r=w/m plays an overriding role.

Design-flow modeling and knowledge-based management

With rapidly growing complexity in the field of design, system engineers and designers are confronted with a constantly increasing variety of highly specialized tools, which have to be integrated and operated. Advanced computer-aided design (CAD) framework techniques are urgently needed to provide infrastructure and support to CAD system engineers as well as designers In this paper, a concept for design-decision support provided by an intelligent design-flow-management component is presented. This support helps to cut down design time, to reduce the error proneness of the design process, and to eliminate the need for highly trained specialists to operate a CAD system. Some aspects with respect to a knowledge-based realization are presented Although the work presented here was primarily intended to make CAD systems more autonomous, we feel that it involves a general process modeling and control technique, which can be exploited for many types of discrete event systems.

Infrastructure for Complex Systems - CAD Frameworks

Designing complex system composed of many different subcomponents is a major challenge in software engineering. This paper deals with the system theoretical aspects of this problem and as a typical example discusses a CAD system for printed circuit boards and application specific integrated circuits. The appropriate infrastructure (framework) for such a system, consisting of a user interface, a data management facility as well as a design management component is presented in detail.

Special feature vector coding and appropriate distance definition developed for a speech recognition system

In this paper a single-word speech-recognition system based on autocorrelation feature vectors is presented. Existing comparable systems use an extra data word for each coefficient of a feature vector. Normally for large vocabularies, vector quantization is performed in order to reduce the resulting large amount of data. Another way to reduce the storage needed is proposed by using a rough vector coefficient quantization instead of vector quantization. If, for example, 16 autocorrelation coefficients coded with two bits each are stored in one 32 bit data word, one obtains, besides an optimal use of the available storage, a good facility of computing a distance between pairs of feature vectors in a very fast way. A modified distance measure based on the cityblock distance is introduced. It only takes about 200 ns to compute one distance with the aid of appropriate programmed read only memories. If coefficient quantization is involved instead of vector quantization and the modified distance measure is used, there is no loss of accuracy. In each case we obtained recognition rates better than 95% for a 250-word recognition system.