This paper proposes two methods that cope with difficulties in connected digit recognition. One is the 'Demi-Word Pair Reference Pattern(DWPR) Method', which is useful for dealing with the coarticulation effect appearing at the word boundaries. The other is the 'Typically Distorted Pattern (TDP) Method'. This helps prepare robust reference templates including several types of distortion which often occur in natural speech. An experiment has been performed for 20 untrained speakers in speaker-dependent mode. The TDP was gathered from multiple speakers' pattern. The results showed that the TDP+DWPR integrated method achieved considerably higher recognition accuracy (99.0%) than a conventional word-based DP-matching method (97.5%).

In this paper, two new algorithms are proposed to overcome demerits in previous algorithms, such as the CWDP algorithm or the One-Pass algorithm. In the first one, called 'Blockwise DP matching (BWDP) algorithm', the calculation is carried out in step with the block having BL input pattern frames, instead of one frame used in the CWDP algorithm. This reduces the number of memory access times to 1/BL. However, it cannot handle the finite state automaton control with loop transition rules. In the other algorithm, called 'Slant-blockwise DP matching (SBDP) algorithm', the calculation block is inclined to the reference pattern time axis. Calculation is carried out in each slant block with BL frame width. This makes it possible to handle the finite state automaton control with loop transition rules. However, the program for this algorithm is rather complex. Further, improvement concerning variable block width is proposed. It can extend the effective block width. Namely, it can further reduce the number of memory access times.

A new single-chip microprocessor for speech recognition, the SRP, has been developed, utilizing a multiprocessor architecture and a pipelined structure. It can recognize up to 340 isolated words or 40 connected words in real time. The SRP contains a vector distance calculator, a DP-equation calculator, and an I/O controller operating in a pipelined manner. Algorithm variations and operation parameters are user programmable, and the total size of the SRP program for a typical speech recognition system is about 700 words. The device has been fabricated with n-channel Si-gate E/D MOS technology with 2.5 μm design rules and employs 7296 three-transistor dynamic RAM cells for a total of more than 40 000 transistors.

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.

In speaker independent word recognition, time-normalization problem has not been completely solved at present. In the attempt to solve this problem, this paper proposes an algorithm which takes into consideration nearly invariant properties in the time axis of the transient parts of the speech. Using this algorithm, speaker independent recognition becomes possible by performing multi-dimensional analysis of the transient parts of the speech after transient detection. This algorithm has been applied to 12-word recognition and 101-monosyllable recognition, showing correct rates of about 98 % and 82 %, respectively, for non-learning data.