The study of the glottal flow, the acoustic excitation for voiced speech, provides insight into the voice signal, which is of potential benefit in many disciplines. One common method for estimating the glottal flow is inverse filtering, in which the effects of the vocal tract and the lip radiation are removed from a microphone signal. This paper presents a new inverse filtering and parameterization software package, which is available under an open-source licence. It provides a user-friendly graphical interface for rapid inverse filtering and parameterization, and the algorithms and parameters can be easily re-used in other projects. The system has already proved to be useful in algorithm development, speech science research, as well as in the study of occupational voice.

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.

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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.

Objective: The goal of the study is to use physical modelling of voice production to assess the performance of an inverse filtering method in estimating the glottal flow from acoustic speech pressure signals. Methods: An automatic inverse filtering method is presented, and speech pressure signals are generated using physical modelling of voice production so as to obtain test vowels with a known shape of the glottal excitation waveform. The speech sounds produced consist of 4 different vowels, each with 10 different values of the fundamental frequency. Both the original glottal flows given by physical modelling and their estimates computed by inverse filtering were parametrised with two robust voice source parameters: the normalized amplitude quotient and the difference (in decibels) between the levels of the first and second harmonics. Results:The results show that for both extracted parameters the error introduced by inverse filtering was, in general, small. The effect of the distortion caused by inverse filtering on the parameter values was clearly smaller than the change in the corresponding parameters when the phonation type was altered. The distortion was largest for high-pitched vowels with the lowest value of the first formant. Conclusions: The study shows that the proposed inverse filtering technique combined with the extracted parameters constitutes a voice source analysis tool that is able to measure the voice source dynamics automatically with satisfactory accuracy.