A standard speaker read linguistically confident and doubtful texts in a confident or doubtful voice. A computer-based acoustic analysis of the four tapes showed that paralinguistic confidence was expressed by increased loudness of voice, rapid rate of speech, and infrequent, short pauses. Under some conditions, higher pitch levels and greater pitch and energy fluctuations in the voice were related to paralinguistic confidence. In a 2 × 2 design, observers perceived and used these cues to attribute confidence and related personality traits to the speaker. Both text and voice cues are related to confidence ratings; in addition, the two types of cue are related to differing personality attributes.
"People have preferences which types of voices they prefer and which they dislike (cf. ). For many technical tasks it is desirable to select voices that appear pleasant or seem likable to a large number of people. "
[Show abstract][Hide abstract] ABSTRACT: Recently, the automatic analysis of likability of a voice has become popular. This work follows up on our original work in this field and provides an in-depth discussion of the matter and an analysis of the acoustic parameters. We investigate the automatic analysis of voice likability in a continuous label space with neural networks as regressors and discuss the relevance of acoustic features. We provide results on the Speaker Likability Database for comparison with previous work and a subset of the TIMIT database for validation.
Proceedings 14th International Workshop on Image and Audio Analysis for Multimedia Interactive Services, WIA²MIS 2013; 07/2013
"For example, both low and high vocal fundamental frequencies (F0) have been associated with dominant behavior , , , while a high F0 was an indicator of submissiveness. There has also been research to show that loudness of the vocal signal, greater pitch and a faster speaking rate is correlated with perceptions of dominance for someone reading both a confident and doubtful piece of text . Faster speaking rate is also indicative of competence, which is also Buller and Aune suggested was linked to dominance . "
[Show abstract][Hide abstract] ABSTRACT: With the increase in cheap commercially available sensors, recording meetings is becoming an increasingly practical option. With this trend comes the need to summarize the recorded data in semantically meaningful ways. Here, we investigate the task of automatically measuring dominance in small group meetings when only a single audio source is available. Past research has found that speaking length as a single feature, provides a very good estimate of dominance. For these tasks we use speaker segmentations generated by our automated faster than real-time speaker diarization algorithm, where the number of speakers is not known beforehand. From user-annotated data, we analyze how the inherent variability of the annotations affects the performance of our dominance estimation method. We primarily focus on examining of how the performance of the speaker diarization and our dominance tasks vary under different experimental conditions and computationally efficient strategies, and how this would impact on a practical implementation of such a system. Despite the use of a state-of-the-art speaker diarization algorithm, speaker segments can be noisy. On conducting experiments on almost 5 hours of audio-visual meeting data, our results show that the dominance estimation is robust to increasing diarization noise.
IEEE Transactions on Audio Speech and Language Processing 06/2011; 19(4-19):847 - 860. DOI:10.1109/TASL.2010.2066267 · 2.48 Impact Factor
"Like high F 0 variation, intensity is a characteristic of high activation emotions—fear, anger, and joy (Banse and Scherer 1996). More confident individuals speak with greater intensity (Kimble and Seidel 1991), and high intensity is associated with perceptions of dominance (Aronovitch 1976; Scherer et al. 1973). "
[Show abstract][Hide abstract] ABSTRACT: Low mean fundamental frequency (F(0)) in men's voices has been found to positively influence perceptions of dominance by men and attractiveness by women using standardized speech. Using natural speech obtained during an ecologically valid social interaction, we examined relationships between multiple vocal parameters and dominance and attractiveness judgments. Male voices from an unscripted dating game were judged by men for physical and social dominance and by women in fertile and non-fertile menstrual cycle phases for desirability in short-term and long-term relationships. Five vocal parameters were analyzed: mean F(0) (an acoustic correlate of vocal fold size), F(0) variation, intensity (loudness), utterance duration, and formant dispersion (D(f), an acoustic correlate of vocal tract length). Parallel but separate ratings of speech transcripts served as controls for content. Multiple regression analyses were used to examine the independent contributions of each of the predictors. Physical dominance was predicted by low F(0) variation and physically dominant word content. Social dominance was predicted only by socially dominant word content. Ratings of attractiveness by women were predicted by low mean F(0), low D(f), high intensity, and attractive word content across cycle phase and mating context. Low D(f) was perceived as attractive by fertile-phase women only. We hypothesize that competitors and potential mates may attend more strongly to different components of men's voices because of the different types of information these vocal parameters provide.
Human Nature 12/2010; 21(4):406-427. DOI:10.1007/s12110-010-9101-5 · 1.96 Impact Factor
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