The objective of this paper is to provide an overview of the recent developments in the area of speech processing and in particular in the fields of speech coding and speech recognition. The speech coding review covers DPCM coders, model-based vocoders, waveform coders, and hybrid coders. The hybrid coders are described in some detail since they are the subject of current research. Our treatment of speech recognition techniques concentrates on the methodologies for voice recognition and the progress made in speaker independent recognition. In addition, we describe the efforts towards commercial deployment of this technology.

This paper investigates the performance of the line spectrum pair (LSP) frequency parameter representation for speech recognition. Transitional parameters of LSP frequencies are defined using first-order regression coefficients. The transitional and the instantaneous frequency parameters are linearly combined to generate a single feature vector used for recognition. The performance of the single vector is compared with that of the cepstral coefficients (CC) representation using a minimumdistance classifier in speaker-independent isolated word recognition experiments. In the speech recognition experiments, the transitional and the instantaneous coefficients are also combined in the distance domain. Also, inverse variance weighted Euclidean measures are defined using LSP frequencies to achieve Mel-scale-like warping and the new warped-frequencies are used in recognition experiments. The performance of the single feature vector defined with transitional and instantaneous LSP frequencies is found to be the best among the measures used in the experiments.

This paper describes the future perspective of automatic telephone interpretation using a multimedia intelligent communication network. The need for language interpretation over a telecommunication system creates a strong drive toward integrating information modalities for voice, image, data, computation and conferencing into modern systems using the capability of language interpretation. An automatic telephone interpretation system will solve the problems of language differences in international human-to-human communication. The future prospective of advanced multimedia language communication will be stated as the versatile application of an integrated intelligent network.

There have been several studies related to a reduction of the amount of computational resources used by Turing machines. As consequences, Linear speed-up theorem", tape compression theorem" and reversal reduction theorem" have been obtained. In this paper, we discuss a leaf reduction theorem on alternating Turing machines. Recently, the result that one can reduce the number of leaves by a constant factor without increasing the space complexity was shown for space- and leaf-bounded alternating Turing machines. We show that for time- and leaf-bounded alternating Turing machines, the number of leaves can be reduced by a constant factor without increasing time used by the machine. Therefore, our result says that a constant factor on the leaf complexity does not affect the power of time- and leaf-bounded alternating Turing machines.