Pitch determination considering laryngealization effects in spoken dialogs

A frequent phenomenon in spoken dialogs of the information seeking type are short elliptic utterances whose mood (declarative or interrogative) can only be distinguished by intonation. The main acoustic evidence is conveyed by the fundamental frequency or F₀ -contour. Many algorithms for F₀ determination have been reported in the literature. A common problem are irregularities of speech known as `laryngealizations´. This article describes an approach based on neural network techniques for the improved determination of fundamental frequency. First, an improved version of the authors´ neural network algorithm for reconstruction of the voice source signal (glottis signal) is presented. Second, the reconstructed voice source signal is used as input to another neural network distinguishing the three classes `voiceless´, `voiced non-laryngealized´, and `voiced laryngealized´. Third, the results are used to improve an existing F₀ algorithm. Results of this approach are presented and discussed in the context of the application in a spoken dialog system