Perception of emotional valences and activity levels from vowel segments of continuous speech.

This study aimed to investigate the role of voice source and formant frequencies in the perception of emotional valence and psychophysiological activity level from short vowel samples (approximately 150 milliseconds). Nine professional actors (five males and four females) read a prose passage simulating joy, tenderness, sadness, anger, and a neutral emotional state. The stress carrying vowel [a:] was extracted from continuous speech during the Finnish word [ta:k:ahan] and analyzed for duration, fundamental frequency (F0), equivalent sound level (L(eq)), alpha ratio, and formant frequencies F1-F4. Alpha ratio was calculated by subtracting the L(eq) (dB) in the range 50 Hz-1 kHz from the L(eq) in the range 1-5 kHz. The samples were inverse filtered by Iterative Adaptive Inverse Filtering and the estimates of the glottal flow obtained were parameterized with the normalized amplitude quotient (NAQ = f(AC)/(d(peak)T)). Fifty listeners (mean age 28.5 years) identified the emotional valences from the randomized samples. Multinomial Logistic Regression Analysis was used to study the interrelations of the parameters for perception. It appeared to be possible to identify valences from vowel samples of short duration ( approximately 150 milliseconds). NAQ tended to differentiate between the valences and activity levels perceived in both genders. Voice source may not only reflect variations of F0 and L(eq), but may also have an independent role in expression, reflecting phonation types. To some extent, formant frequencies appeared to be related to valence perception but no clear patterns could be identified. Coding of valence tends to be a complicated multiparameter phenomenon with wide individual variation.

TKK Aparat: an environment for voice inverse filtering and parameterization.

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.

Comparison of two inverse filtering methods in parameterization of the glottal closing phase characteristics in different phonation types.

SUMMARY: Inverse filtering (IF) is a common method used to estimate the source of voiced speech, the glottal flow. This investigation aims to compare two IF methods: one manual and the other semiautomatic. Glottal flows were estimated from speech pressure waveforms of six female and seven male subjects producing sustained vole /a/ in breathy, normal, and pressed phonation. The closing phase characteristics of the glottal pulse were parameterized using two time-based parameters: the closing quotient (C1Q) and the normalized amplitude quotient (NAQ). The information given by these two parameters indicates a strong correlation between the two IF methods. The results are encouraging in showing that the parameterization of the voice source in different speech sounds can be performed independently of the technique used for inverse filtering.

An amplitude quotient based method to analyze changes in the shape of the glottal pulse in the regulation of vocal intensity.

This study presents an approach to visualizing intensity regulation in speech. The method expresses a voice sample in a two-dimensional space using amplitude-domain values extracted from the glottal flow estimated by inverse filtering. The two-dimensional presentation is obtained by expressing a time-domain measure of the glottal pulse, the amplitude quotient (AQ), as a function of the negative peak amplitude of the flow derivative (d(peak)). The regulation of vocal intensity was analyzed with the proposed method from voices varying from extremely soft to very loud with a SPL range of approximately 55 dB. When vocal intensity was increased, the speech samples first showed a rapidly decreasing trend as expressed on the proposed AQ-d(peak) graph. When intensity was further raised, the location of the samples converged toward a horizontal line, the asymptote of a hypothetical hyperbola. This behavior of the AQ-d(peak) graph indicates that the intensity regulation strategy changes from laryngeal to respiratory mechanisms and the method chosen makes it possible to quantify how control mechanisms underlying the regulation of vocal intensity change gradually between the two means. The proposed presentation constitutes an easy-to-implement method to visualize the function of voice production in intensity regulation because the only information needed is the glottal flow wave form estimated by inverse filtering the acoustic speech pressure signal.

Emotions in vowel segments of continuous speech: analysis of the glottal flow using the normalised amplitude quotient.

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 parameterized 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.

Emotions in [a]: a perceptual and acoustic study.

The aim of this investigation is to study how well voice quality conveys emotional content that can be discriminated by human listeners and the computer. The speech data were produced by nine professional actors (four women, five men). The speakers simulated the following basic emotions in a unit consisting of a vowel extracted from running Finnish speech: neutral, sadness, joy, anger, and tenderness. The automatic discrimination was clearly more successful than human emotion recognition. Human listeners thus apparently need longer speech samples than vowel-length units for reliable emotion discrimination than the machine, which utilizes quantitative parameters effectively for short speech samples.

Estimation of the voice source from speech pressure signals: evaluation of an inverse filtering technique using physical modelling of voice production.

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.