Fundamental microwave key devices used in achieving compact mobile/portable telephones (raidio units) are discussed. The historical development flow of the systems and radio units are introduced, with respect to the 800-/900-MHz and 1.5-GHz Japanese cellular radio systems. The design concept of the developed radio units is briefly described. Tehnical requirements for RF circuits are reviewed and the developed key devices are practically applied to the circuits. Key factors in the requirements are also shown. Finally. future trends fro the key devices are surveyed from the stand point of achieving a smaller and more light weight pocket radio unit.

We are aming to develop a computer-based consultant system which helps novice computer users to achieve their task goals on computers through natural language dialogues. Our target is spoken Japanese. To develop effective methods for processing spoken Japanese, it is essential to analyze real dialogues and to find the characteristics of spoken Japanese. In this paper, we discuss the design problems associated with constructing a spoken dialogue database from the viewpoint of advisory dialogue collection, describe XMH (X-window-based electronic mail handling program) usage experiments made to collect advisory dialogues between novice XMH users and an expert consultant, and show the dialogue database we constructed from these dialogues. The main features of our database are as follows: (1) Our target dialogues were advisory ones. (2) The advisory dialogues were all related to the use of XMH that has a visual interface operated by a keyboard and a mouse. (3) The primary objective of the users was not to engage in dialogues but to achieve specific task goals using XMH. (4) Not only what the users said but also XMH operations performed by the users are included as dialogue elements. This kind of dialogue database is a very effective source for developing new methods for processing spoken language in multimodal consultant systems, and we have therefore made it available to the public. Based on our analysis of the database, we have already developed several effective methods such as a method for recognizing user's communicative intention from a transcript of spoken Japanese, and a method for controlling dialogues between a novice XMH user and the computer-based consultant system which we are developing. Also, we have proposed several response generation rules as the response strategy for the consultant system. We have developed an experimental consultant system by implementing the above methods and strategy.

An automatic zip code recognition system for Japanese mail is proposed in this paper. It is assumed that a zip code is composed of three numerals and requited to be written in a specified frame. In actual images, however, the three numerals sometimes extend outside the specified frame and are not clearly separated. Considering this situation, the authors devised a system with two stages, the segmentation stage and the recognition stage. The segmentation stage consists of five steps: setting and adjusting of initial areas for numeral images (figures), calculation of the center of gravity of each figure, search for the horizontal and vertical boundaries of each figure, determination of the final area for each figure, and normalization of the figure in each final area. In the recognition stage, the Localized Arc Pattern Method (Arc method) proposed by Yoshimura et al. (1991) is implemented hierarchically; that is, a simple Arc method is applied first to each figure and a more complex one is applied subsequently unless the figure is identified in the first step. In the recognition process, every figure is judged as a numeral or otherwise rejected. The proposed system was applied to a database provided by the Institute for Post and Telecommunications Policy (IPTP). The segmentation algorithm yielded an adequate result. The recognition algorithm yielded scores as high as 90.6% in correct recognition rate and 0.7% in error rate. The best score of the precision index (P-index) specified by the IPTP was as low as 15.7 for the above mentioned IPTP database, while the score for another IPTP database was 16.9.

An integrated pen interface system was developed to allow effective Japanese text entry. It consists of sub-systems for handwriting recognition, contextual post-processing, and enhanced Kana-to-Kanji conversion. The recognition sub-system uses a hybrid algorithm consisting of a pattern matcher and a neural network discriminator. Special care was taken to improve the recognition of non-Kanji and simple Kanji characters frequently used in fast data entry. The post-processor predicts consecutive characters on the basis of bigrams modified by the addition of parts of speech and substitution of macro characters for Kanji characters. A Kana-to Kanji conversion method designed for ease of use with a pen interface has also been integrated into the system. In an experiment in which 2,900 samples of Kanji and non-Kanji characters were obtained from 20 subjects, it was observed that the original recognition accuracy of 83.7% (the result obtained by using the pattern matching recognizer) was improved to 90.7% by adding the neural network discriminator, and that it was further improved to 94.4% by adding the post-processor. The improved recognition accuracy for non-Kanji characters was particularly marked.

This paper proposes an off-line text-independent writer identification method applicable to Japanese and Korean sentences. It is assumed that the writer of a writing in question exists in a certain group of people and that reference writings written by each person in the group can be used for identification. In the proposed method, relative frequencies of some model patterns are counted on the binary pattern of each writing and are used as the feature to measure the distance between two writings. Based on a modified Mahalanobis' distance for this feature, the person whose reference writing is nearest to the writing in question is judged as the writer. The effectiveness of the proposed method is examined through an experiment using Japanese and Korean writings. Error rates in the experiment were different depending on conditions such as volume of reference writings, dimension of adopted features, and number of people to be identified. In some cases, error rates as low as 0% were observed. Error rates tend to be lower in Korean writings probably because Hangul is composed of a smaller number of letters compared to Kanji and Hiragana in Japanese writing.

A unification-based Japanese parser has been implemented for an experimental Japanese-to-English spoken language translation system (SL-TRANS). The parser consists of a unification-based spoken-style Japanese grammar and an active chart parser. The grammar handles the syntactic, semantic, and pragmatic constraints in an integrated fashion using HPSG-based framework in order to cope with speech recognition errors. The parser takes multiple sentential candidates from the HMM-LR speech recognizer, and produces a semantic representation associated with the best scoring parse based on acoustic and linguistic plausibility. The unification-based parser has been tested using 12 dialogues in the conference registration domain, which include 261 sentences uttered by one male speaker. The sentence recognition accuracy of the underlying speech recognizer is 73.6% for the top candidate, and 83.5% for the top three candidates, where the test-set perplexity of the CFG grammar is 65. By ruling out erroneous speech recognition results using various linguistic constraints, the parser improves the sentence recognition accuracy up to 81.6% for the top candidate, and 85.8% for the top three candidates. From the experiment result, we found that the combination of syntactic restriction, selectional restriction and coordinate structure restriction can provide a sufficient restriction to rule out the recognition errors between case-marking particles with the same vowel, which are the type of errors most likely to occur. However, we also found that it is necessary to use pragmatic information, such as topic, presupposition, and discourse structure, to rule out the recognition errors involved with topicalizing particles and sentence final particles.