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Technologies related to applications can be divided into two categories. One is system technologies and the other is speech recognition and synthesis algorithms.

Hardware and software technologies are the main topics for system development. Hardware technologies are very important because any speech algorithm is destined for implementation on hardware. Technology in this area is advancing quickly. Microprocessors with capacities of about 100 MIPS are available. Also, digital signal processors (DSPs) that have capabilities of nearly 50 MFLOPS have been developed (Dyer and Harms, 1993) for numerical calculations dedicated to voice processing. Almost all speech recognition/synthesis algorithms can be used with a microprocessor and several DSPs. With the progress of device technology and parallel architecture, hardware technology will continue to improve and will be able to cope with the huge number of calculations demanded by improved algorithms of the future.

Also, software technologies are an important factor, as algorithms and application procedures should be implemented by the use of software technology. In this paper, therefore, software technology will be treated as an application development tool. Along with the growth areas of application of voice-processing technology, various architectures and tools that support applications development have been devised. This architecture and these tools range from compilers for developing DSP firmware to software development tools that enable users to develop dedicated software from application specifications. Also, when speech processing is the application target, it is important to keep in mind the characteristics peculiar to speech. Speech communication basically is of a nature that it should work in a real-time interactive mode. Computer systems that handle speech communications with users should have an ability to cope with these operations. Several issues concerning real-time interactive communication will be described.

For algorithms there are two important issues concerning application. One is the evaluation of algorithms, and the other is the robustness of algorithms under adverse conditions. Evaluation of speech recognition and synthesis algorithms has been one of the main topics in the research area. However, to consider applications, these algorithms should be evaluated in real situations rather than laboratory situations, which is a new research trend. There are two recent improvements in algorithm evaluation. First, algorithm evaluation using large-scale speech databases, which are developed and shared by many research institutions, means that various types of algorithms can be more easily and extensively compared. The second improve-



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