End‐point detection of speech using spectral transition for captioning system

Abstract

In recent years, captioning video contents with text translations is increasingly necessary because of the burgeoning use of media internationally, resulting from the rapid development of communication technology. In addition, within one language, video captioning is very important for hearing‐impaired people. However, the process of captioning videos, including speech and nonspeech decisions, is often done manually by translators at present. Therefore, an efficient automatic end‐point detection of speech for captioning video contents has been proposed. We attempted to detect speech end‐points based on acoustic landmarks that identify times when acoustic changes are prominent in the speech signals [K. N. Stevens, Acoust. Phonetics (1998)]. In this study, landmarks were obtained by combining the mean square for the regression coefficients of logarithmic envelopes of 1/3‐oct bands in time, which resembles the parameter proposed by Furui to measure spectral transition [S. Furui, J. Acoust. Soc. Am. 80(4), 1016–1025 (1986)], with other ones such as the logarithmic power of speech signals. An experiment was carried out using the proposed technique for speech detection. Results showed a high correct rate and introduced the possibility of its application to an efficient video captioning system. [Work partially supported by Open Research Center Project from MEXT.]