The performance of parallel combinatory spread spectrum (PC/SS) communication systems in the frequency-nonselective, slowly Rayleigh fading channel is studied. Performance is evaluated by symbol error rate using numerical computation. To overcome the performance degradation caused by fading, we also studied the effects of selection diversity and Reed-Solomon coding applied to the PC/SS system. As a result, a remarkable improvement in error rate performance is achieved with Reed-Solomon coding and diversity technique. The coding rate for the maximum coding gain is almost a half of that in the additive white gaussian noise channel.

In this paper, we present a unified model for dialogue understanding involving various sorts of ambiguities, such as lexical, syntactic, semantic, and plan ambiguities. This model is able to estimate and revise the most preferable interpretation of utterances as a dialogue progresses. The model's features successfully capture the dynamic nature of dialogue management. The model consists of two main portions: (1) an extension of first-order logic for maintaining multiple interpretations of ambiguous utterances in a dialogue; (2) a device which estimates and revises the most preferable interpretation from among these multiple interpretations. Since the model is logic-based, it provides a good basis for formulating a rational justification of its current interpretation, which is one of the most desirable aspects in generating helpful responses. These features (contained in our model) are extremely useful for interactive dialogue management.

This paper describes the concepts and methodologies of the INTELLITUTOR system which is an integrated intelligent programming environment for learning programming. INTELLITUTOR attempts to work as a human programming tutor to guide a user, i.e., a student, in writing a computer program, to detect logical errors within it, and to make advices not only for fixing them but also for letting him notice his misunderstandings. The system consists of three major modules, i.e., GUIDE, ALPUS and TUTOR. GUIDE is a guided editor for easy coding, ALPUS is an algorithm-based program understander, and TUTOR is an embedded-intelligent tutoring system for programming education. The ALPUS system can infer user's intentions from buggy codes in addition to detecting logical errors by means of knowledge-based reasoning. ALPUS uses four kinds of programming knowledge: 1) knowledge on algorithms, 2) Knowledge on programming techniques, 3) Knowledge on a programming language, and 4) Knowledge on logical errors. These knowledge are organized in a hierarchical procedure graph (HPG) as a multi-use knowledge base. The knowledge on logical errors was obtained by means of cognitive experiments. The student model is built by means of the results of ALPUS and interactions between a student and the system. Teaching is done based on the student model. Because the ITS subsystem, i.e., TUTOR, is embedded within the intelligent programming environment interactions for creating the student model could be minimized. Although the current system deals with the PASCAL language, most of the knowledge is applicable to those of procedure-oriented programming languages. The INTELLITUTOR system was implemented in the frame-based knowledge engineering environment ZERO and working on a UNIX workstation for system evaluation.

This paper describes a method for describing a three-dimensional (3-D) scene by integrating color and range data. Range data is obtained by a feature-based stereo method developed in our laboratory. A color image is segmented into uniform color regions. A plane is fitted to the range data inside a segmented region. Regions are classified into three types based on the range data. A certain types of regions are merged and the others remain unless the region type is modified. The region type is modified if the range data on a plane are selected by removing of the some range data. As a result, the scene is represented by planar surfaces with homogeneous colors. Experimental results for real scenes are shown.

This paper deals with the theory and design method of an efficient radix-4 divider using carry-propagation-free adders based on redundant binary {-1,0,+1} representation. The usual method of normalizing the divisor in the range [1/2,1) eliminates the advantages of using a higher radix than two, bacause many digits of the partial remainder are required to select the quotient digits. In the radix-4 case, it is shown that it is possible to select the quotient digits to refer to only the four (in the usual normalizing method it is seven) most significant digits of the partial remainder, by scaling the divisor in the range [12/8,13/8). This leads to radix-4 dividers more effective than radix-2 ones. We use the hyperstring graph representation proposed in Ref.(18) for redundant binary adders.

A context-sensitive method to predict linguistic expressions in the next utterance in inquiry dialogues is proposed. First, information of the next utterance, the utterance type, the main action and the discourse entities, can be grasped using a dialogue interpretation model. Secondly, focusing in particular on dialogue situations in context, a domain-dependent knowledge-base for literal usage of both noun phrases and verb phrases is developed. Finally, a strategy to make a set of linguistic expressions which are derived from semantic concepts consisting of appropriate expressions can be used to select the correct candidate from the speech recognition output. In this paper, some of the processes are particularly examined in which sets of polite expressions, vocatives, compound nominal phrases, verbal phrases, and intention expressions, which are common in telephone inquiry dialogue, are created.

This paper discusses the problems facing spoken dialogue processing and the prospects for future improvements. Research on elemental topics like speech recognition, speech synthesis and language understanding has led to improvements in the accuracy and sophistication of each area of study. First, in order to handle a spoken dialogue, we show the necessity for information exchanges between each area of processing as seen through the analysis of spoken dialogue characteristics. Second, we discuss how to integrate those processes and show that the memory-basad approach to spontaneous speech interpretation offers a solution to the problem of process integration. The key to this is setting up a mental state affected by both speech and linguistic information. Finally, we discuss how those mental states are structured and a method for constructing them.

This paper describes design issues of a speech dialogue system, the evaluation of the system, and the data collection of spontaneous speech in a transportation guidance domain. As it is difficult to collect spontaneous speech and to use a real system for the collection and evaluation, the phenomena related with dialogues have not been quantitatively clarified yet. The authors constructed a speech dialogue system which operates in almost real time, with acceptable recognition accuracy and flexible dialogue control. The system was used for spontaneous speech collection in a transportation guidance domain. The system performance evaluated in the domain is the understanding rate of 84.2% for the utterances within the predefined grammar and the lexicon. Also some statistics of the spontaneous speech collected are given.

This paper describes a task-oriented speech dialogue system based on spontaneous speech understanding and response generation (TOSBURG). The system has been developed for a fast food ordering task using speaker-independent keyword-based spontaneous speech understanding. Its purpose being to understand the user's intention from spontaneous speech, the system consists of a noise-robust keyword-spotter, a semantic keyword lattice parser, a user-initiated dialogue manager and a multimodal response generator. After noise immunity keyword-spotting is performed, the spotted keyword candidates are analyzed by a keyword lattice parser to extract the semantic content of the input speech. Then, referring to the dialogue history and context, the dialogue manager interprets the semantic content of the input speech. In cases where the interpretation is ambiguous or uncertain, the dialogue manager invites the user to confirm verbally the system's understanding of the speech input. The system's response to the user throughout the dialogue is multimodal; that is, several modes of communication (synthesized speech, text, animated facial expressions and ordered food items) are used to convey the system's state to the user. The object here is to emulate the multimodal interaction that occurs between humans, and so achieve more natural and efficient human-computer interaction. The real-time dialogue system has been constructed using two general purpose workstations and four DSP accelerators (520MFLOPS). Experimental results have shown the effectiveness of the newly developed speech dialogue system.

Resolving ambiguities in interpreting the user's utterances is one of the most fundamental problems in the development of a question-answering system. The process of disambiguating interpretations requires knowledge and inference functions on an objective task field. This paper describes a framework for understanding conversational language, using the multi-paradigm knowledge representation (frames" and rules") which represents concept hierarchy and causal relationships for an objective field. Knowledge of the objective field is used in the process to interpret input sentences as a model for the objective world. In interpreting sentences, a procedure judges preferences for interpretation candidates by identifying causal relationship with messages in the preceding context, where the causal relationship is used to supplement some shortage of information and to give either an affirmative or a negative explanation to the interpretation. The procedure has been implemented in an experimental question-answering system, whose current task is consultation in operating an electronic device. The experimental results are shown for a concrete problem involving resolving anaphoric references, and characteristics of the knowledge processing system are discussed.