This study deals with the relevance of spectral emphasis for accent detection. Spectral emphasis may be described as an acoustic feature reflecting the relative intensity in the higher frequency bands. In an experiment using a rudimentary accent detector, spectral emphasis was shown to be more useful for the detection of accents than overall intensity. Furthermore, spectral emphasis was found to outperform f 0 in certain conditions. It is argued here, therefore, that it might be worthwhile to include spectral emphasis in systems using a combination of acoustic features for automatic classification of prosodic categories.

A large sample of vowels produced by male and female speakers were inverse filtered and parameterized using 21 different glottal flow parameters. The performance of the different parameters in expression of the phonation type was then tested using objective statistical methods. The comparison of the results revealed marked differences in the parameters ’ performance, and therefore, guidelines for parameter use and comparison were established. Index Terms: voice quality, phonation type, inverse filtering, voice source, parameterization

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Emotions in short vowel segments of continuous speech were analysed using inverse filtering and a recently developed glottal flow parameter, the normalised amplitude quotient (NAQ). Simulated emotion portrayals were produced by 9 professional stage actors. Separated /a: / vowel segments were inverse filtered and parameterised using NAQ. Statistical analyses showed significant differences among most of the emotions studied. Results also demonstrated clear gender differences. Inverse filtering, together with NAQ, was shown to be a promising method for the analysis of emotional content in continuous speech. Copyright © 2006 S. Karger AG, Basel 1

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Voice quality, defined by John Laver as the characteristic auditory colouring of a speaker’s voice, is a significant feature of speech, and it is used to signal various properties such as emotions, intentions, and mood of the speaker. While voice quality measurement techniques and algorithms have been developed, much work is needed to obtain a comprehensive view of the function and analysis of human voice in the production of different voice qualities. Two major research questions are presented in this thesis: First, how can the most important laryngeal voice quality features be analyzed, and second, how do the voice quality features affect different facets of vocal expression? To answer these questions, five separate studies of the analysis methodology and two studies regarding the voice quality behaviour were

This paper describes a new algorithm for automatically detecting creak in speech signals. Detection is made by utilising two new acoustic parameters which are designed to characterise creaky excitations following previous evidence in the literature combined with new insights from observations in the current work. In particular the new method focuses on features in the Linear Prediction (LP) residual signal including the presence of secondary peaks as well as prominent impulse-like excitation peaks. These parameters are used as input features to a decision tree classifier for identifying creaky regions. The algorithm was evaluated on a range of read and conversational speech databases and was shown to clearly outperform the state-of-the-art. Further experiments involving degradations of the speech signal demonstrated robustness to both white and babble noise, providing better results than the state-of-the-art down to at least 20 dB signal to noise ratio. Keywords: Creak, Creaky voice, vocal fry, glottal source, glottal closure instant