Seibi Chiba

Speech recognition system with delayed output

In a speech recognition system of the type including a recognition unit responsive to a voice input and a conditioning input for recognizing the voice input to produce a recognition output, a start signal is produced whenever a voice input exceeds a threshold level and a pause interval detection signal is produced whenever a voice input falls below a threshold level. An output timing signal is produced when the detection signal lasts a preselected interval of time that may be either about 250 milliseconds or about 250 milliseconds plus a delay. The recognition output from the recognition unit produced in response to the detection signal is displayed in response also to the detection signal. The result is delivered to a utilization device in response to the output timing signal. The delay may be given either by a predetermined duration or an interval between those instants at which the above-mentioned 250 milliseconds have just elapsed after production of the detection signal and after production of another pause interval detection signal for a next following voice input. During the delay, it is possible either by a manually operable switch or a cancel voice input to cancel delivery of the recognition result displayed to be incorrect.

A microprocessor for speech recognition

A new single-chip microprocessor for speech recognition has been developed utilizing multi-processor architecture and pipelined structure. By DP-matching algorithm, the processor recognizes up to 340 isolated words or 40 connected words in realtime.

A speaker-independent word-recognition system using multiple classification functions☆

Abstract A speaker-independent word-recognition system has been developed using multiple classification functions for separating 100 spoken words. The speech signal is first analysed and then non-uniformly time-sampled by referring to word-structure tables to construct a word pattern vector of 120 dimensions. Equivalently piece-wise quadratic classification functions are calculated based on a linear-programming algorithm using a large number of spoken-word design samples. A hardware system for real-time recognition has been built as a high-speed microprocessor complex. Using the classification functions calculated from design samples of 100 speakers, a recognition rate of 99% has been obtained for 50 unknown speakers.