Abstract: The data processing device 400 of this invention comprises a controller unit 402, a data recorder unit 404, a display unit 406, a data input unit 408 and a communication control unit 410. By transmitting a request for service in a multiple-address way to a plurality of devices on a network and selecting a service providing device, communicability with the service-providing group can be automatically obtained without prior registration of device information in the respective devices or in any specified device. If the service providing device withdraws from the network or a trouble develops in the communication link, a new service providing device is selected from among other communicable devices.

Abstract: Communication control apparatus capable of communicating among plural users when the plural users bring respective equipment into proximity of each other includes a transmission section to transmit terminal discriminating information to discriminate a particular terminal. A receiving section receives terminal discriminating information transmitted by another terminal or terminals. A discrimination section discriminates other terminal(s) capable of communicating with the particular terminal in accordance with the terminal discriminating information received by the receiving section. A group-set section sets one terminal or plural terminals among terminals discriminated by the discrimination means as members of the same group. An information sending section sends the same information to the terminals set by the group-set means.

Abstract: The data processing device 400 of this invention comprises a controller unit 402, a data recorder unit 404, a display unit 406, a data input unit 408 and a communication control unit 410. By transmitting a request for service in a multiple-address way to a plurality of devices on a network and selecting a service providing device, communicability with the service-providing group can be automatically obtained without prior registration of device information in the respective devices or in any specified device. If the service providing device withdraws from the network or a trouble develops in the communication link, a new service providing device is selected from among other communicable devices.

Abstract: A digital computing apparatus for preparing document text includes a sentence significance decision section for calculating a significance value of each sentence of document data according to a relation between each sentence and other sentences of the document data. The apparatus can also include a topic extraction section for extracting a topic for each sentence of the document data. A format structure extraction section extracts format structure from document data according to predetermined rules. The format structure, corresponding sentence significance values and topics are sent to an output section. The output section displays this information to the user. The sentence retrieval section retrieves sentences including a user inputted reference word from document data. Then the sentence retrieval section selects a sentence which is related to the reference word from retrieved sentences according to the sentence significance value or the topic. The output section displays only the selected sentence to user.

Abstract: An acoustic pattern of continuous input speech is divided by an acoustic analyzer into frames of a predetermined time interval. A similarity calculator calculates similarities between frame data and the reference phonemic labels prestored in a dictionary memory, and supplies similarity data to a main processor, which has memories prestores speech duration data and connectability data. The main processor extracts, from among the references phonemic labels, those which satisfy phonetic/phonological conditions with respect to phonemes of the input speech. Similarity sum calculation is conducted only for the similarity data of the extracted labels.

Abstract: Continuous speech is input to an acoustic analyzer comprising a filter bank which filters (acoustically analyzes) the input speech and outputs from each filter a characteristic parameter vector of the input speech. The acoustic analyzer also calculates a steadiness parameter which is proportional to a reciprocal of a change in the spectrum of the input speech and represents steadiness of the input speech. the feature parameter vector is input to an initial similarity calculator, and a similarity (initial similarity) to each reference phoneme pattern stored in a reference phoneme pattern memory is calculated using a multiple similarity method. The initial similarity is input to a similarity normalizing circuit, and is normalized (weighted) based on the steadiness parameter in order to reflect information representing steadiness or unsteadiness of a phoneme into the similarity.

Abstract: Speech recognition is improved by first recognizing a sequence of phonemes, then generating a compatibility coefficient between two continuous phonemes to modify the similarity measurements. The compatibility coefficient is varied for a plurality of modified similarity measurements to further improve recognition accuracy.

Abstract: Continuous speech signal is recognized using "rough" and "detail" parameters derived from prestored reference speech and current unknown speech. The detail parameters are 16 spectral coefficients, the rough parameters 2 or 4 spectral coefficients representing the signal. A word interval detector decides segmentation based on rough parameter similarity.

Abstract: A continuous speech recognition circuit has a data generating circuit for calculating feature pattern data each having N-frame feature parameter data of a plurality of word-periods and reference pattern data every time one-frame period has elapsed and for sequentially generating a maximal similarity data among the calculated similarity data, and a recognition circuit for detecting a series of continuous word-periods which gives the largest similarity sum within a speech interval in accordance with the similarity data from the data generating circuit and recognizing as effective word data the word series corresponding to the detected series of continuous word-periods. The similarity data in each word period is obtained by calculating partial similarity data between the feature parameter data of each frame and each reference parameter data and using the N partial similarity data obtained during the word-period.