Automatically assessing acoustic manifestations of personality in speech

Polzehl, Tim; Möller, Sebastian; Metze, Florian

doi:10.1109/slt.2010.5700814

Cited by 21 publications

(28 citation statements)

References 4 publications

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“…It is clear in the literature that some traits can be more easily recognized by means of automatic procedures than others, but this fact may vary according to the data and the methodologies applied (see [21] for a survey). Moreover, it has been timidly pointed out that different personality dimensions/traits are revealed in spontaneous speech by means of different sets of representative acoustic/prosodic features [11,[14][15][16]21], but exhaustive categorizations of such features and studies on their impact across ages, cultures, etc. are still missing.…”

Section: Introductionmentioning

confidence: 99%

Acoustic-Prosodic Automatic Personality Trait Assessment for Adults and Children

Solera-Ureña

Moniz

Batista

et al. 2016

Advances in Speech and Language Technologies for Iberian Languages

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Abstract. This paper investigates the use of heterogeneous speech corpora for automatic assessment of personality traits in terms of the BigFive OCEAN dimensions. The motivation for this work is twofold: the need to develop methods to overcome the lack of children's speech corpora, particularly severe when targeting personality traits, and the interest on cross-age comparisons of acoustic-prosodic features to build robust paralinguistic detectors. For this purpose, we devise an experimental setup with age mismatch utilizing the Interspeech 2012 Personality Subchallenge, containing adult speech, as training data. As test data, we use a corpus of children's European Portuguese speech. We investigate various features sets such as the Sub-challenge baseline features, the recently introduced eGeMAPS features and our own knowledge-based features. The preliminary results bring insights into cross-age and -language detection of personality traits in spontaneous speech, pointing out to a stable set of acoustic-prosodic features for Extraversion and Agreeableness in both adult and child speech.

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Section: Introductionmentioning

confidence: 99%

Acoustic-Prosodic Automatic Personality Trait Assessment for Adults and Children

Solera-Ureña

Moniz

Batista

et al. 2016

Advances in Speech and Language Technologies for Iberian Languages

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show abstract

“…As can be seen from the figure, the coding found in our data correlates quite well with the NEO-FFI coding scheme, as most factors with the same colour (original loadings) point in a similar direction (new factor loadings). This interpretation is also supported by a low number of cross-loadings between factors, and a low to moderate commonality for almost all items [22].…”

Section: Human Perception Of Personality In Speechmentioning

confidence: 72%

“…In [22], we present results of an automatic assessment of all five NEO-FFI traits. In the following, we will give a brief overview of our approach, and our results.…”

Section: Recognizing Personality In Speechmentioning

confidence: 99%

A Review of Personality in Voice-Based Man Machine Interaction

Metze

Black

Polzehl

2011

Lecture Notes in Computer Science

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Abstract. In this paper, we will discuss state-of-the-art techniques for personality-aware user interfaces, and summarize our own recent work in automatically recognizing and synthesizing speech with "personality". We present an overview of personality "metrics", and show how they can be applied to the perception of voices, not only the description of personally known individuals. We present use cases for personality-aware speech input and/ or output, and discuss approaches at defining "personality" in this context. We cover the state of the art in recognizing personality from speech, using an approach, which is very similar to other meta-data extraction schemes. We also discuss the difficulty of generating appropriate responses in an automatic dialog system, including work on generating consistency of what is being said, and how it is being said. To conclude, we present speculations about the future of this exciting area of ongoing research.

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“…It is clear in the literature that some traits can be more easily recognized by means of automatic procedures than others, but this fact may vary according to the data and the methodologies applied (see [2] for a survey). Moreover, it has been timidly pointed out that different personality traits are revealed in spontaneous speech by means of different sets of representative acoustic/prosodic features [2,3,4,5,6], but exhaustive categorizations of such features and studies across ages, cultures, etc. are still very scarce.…”

Section: Introductionmentioning

confidence: 99%

A Semi-Supervised Learning Approach for Acoustic-Prosodic Personality Perception in Under-Resourced Domains

et al. 2017

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Automatic personality analysis has gained attention in the last years as a fundamental dimension in human-to-human and human-to-machine interaction. However, it still suffers from limited number and size of speech corpora for specific domains, such as the assessment of children's personality. This paper investigates a semi-supervised training approach to tackle this scenario. We devise an experimental setup with age and language mismatch and two training sets: a small labeled training set from the Interspeech 2012 Personality Sub-challenge, containing French adult speech labeled with personality OCEAN traits, and a large unlabeled training set of Portuguese children's speech. As test set, a corpus of Portuguese children's speech labeled with OCEAN traits is used. Based on this setting, we investigate a weak supervision approach that iteratively refines an initial model trained with the labeled data-set using the unlabeled data-set. We also investigate knowledge-based features, which leverage expert knowledge in acoustic-prosodic cues and thus need no extra data. Results show that, despite the large mismatch imposed by language and age differences, it is possible to attain improvements with these techniques, pointing both to the benefits of using a weak supervision and expert-based acoustic-prosodic features across age and language.

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Automatically assessing acoustic manifestations of personality in speech

Cited by 21 publications

References 4 publications

Acoustic-Prosodic Automatic Personality Trait Assessment for Adults and Children

Acoustic-Prosodic Automatic Personality Trait Assessment for Adults and Children

A Review of Personality in Voice-Based Man Machine Interaction

A Semi-Supervised Learning Approach for Acoustic-Prosodic Personality Perception in Under-Resourced Domains

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