Sharlene A. Liu
Res. Lab of Electron., Dept. of Elec. Eng. and Comput. Sci., MIT, Rm. 36-511, Cambridge, MA 02139
Locating landmarks, or acoustically important points, in an utterance is the first step in a proposed method for feature-based speech recognition. The algorithm developed here is designed to locate landmarks caused by closures and releases of obstruent consonants (sounds produced with a pressure buildup behind a constriction) flanked by sonorants. Two characteristics of obstruents are: (1) voicing diminishes or stops completely at the onset and (2) noise is generated during the constricted interval (at the release in the case of stops and affricates). The algorithm thus monitors voicing changes by keeping track of low-frequency signal energy and locates a landmark wherever a rapid change occurs. It also monitors higher frequencies for the presence of noise to aid in the detection of voiceless stop and affricate releases. With appropriate selection of time windows, smoothing intervals, and frequency bands, sonorant/obstruent boundaries for stops, fricatives, and affricates could be detected with only a few percent error. Semivowels and creaky voicing sometimes mistakenly cause a landmark to be detected, but more detailed analysis of the characteristics of these erroneous landmarks may overcome this problem. [Work supported by NSF.]