Automated prediction and analysis of job interview performance: The role of what you say and how you say it

Naim, Iftekhar; Tanveer, Md. Iftekhar; Gildea, Daniel; Hoque, Mohammed Ehsan

doi:10.1109/fg.2015.7163127

Cited by 94 publications

(69 citation statements)

References 19 publications

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“…They also reported R 2 of 0.10 for persuasive and no predictability for communicative. In another work, [23] reported results on a different set of social variables using correlation coefficient r as their evaluation metric. We compare our results to this work by converting r to R 2 (our evaluation metric, coefficient of determination R 2 is obtained by computing the square of correlation coefficient r).…”

Section: Inference Of First Impressionsmentioning

confidence: 99%

“…Speaking Activity: cues such as pauses and speaking time are known to impact hireability impression ratings [23]. We extracted the following activity cues based on the speaker segmentation provided by the Microcone and utilized various statistics like count, mean, standard deviation, and maximum as features.…”

Section: Audio Featuresmentioning

confidence: 99%

“…Further research also examined the relationships between body activity, personality and hireability using a mixture of automatically and manually extracted features [26]. Naim et al [23] extended these works by analyzing a dataset of 138 simulated job interviews from 69 internship seeking students, where they extracted cues related to facial expressions, verbal content, and prosody to predict several social variables (e.g., hiring recommendation, engagement, friendliness) and perceived behaviors (e.g., smile, eye contact, speaking rate).…”

Section: Related Workmentioning

confidence: 99%

“…In the context of job interviews, recent studies have established the feasibility of automatically inferring interview ratings [24] and other related constructs (e.g. engagement, friendliness, or excitement) [23] up to a certain level. Other researchers [17] have extended these works by developing a social coaching system to enable potential job-seekers to train their behavior in order to convey a more positive first impression to recruiters.…”

Section: Introductionmentioning

confidence: 99%

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Training on the job: behavioral analysis of job interviews in hospitality

Muralidhar

Nguyen

Frauendorfer

et al. 2016

Proceedings of the 18th ACM International Conference on Multimodal Interaction

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First impressions play a critical role in the hospitality industry and have been shown to be closely linked to the behavior of the person being judged. In this work, we implemented a behavioral training framework for hospitality students with the goal of improving the impressions that other people make about them. We outline the challenges associated with designing such a framework and embedding it in the everyday practice of a real hospitality school. We collected a dataset of 169 laboratory sessions where two role-plays were conducted, job interviews and reception desk scenarios, for a total of 338 interactions. For job interviews, we evaluated the relationship between automatically extracted nonverbal cues and various perceived social variables in a correlation analysis. Furthermore, our system automatically predicted first impressions from job interviews in a regression task, and was able to explain up to 32% of the variance, thus extending the results in existing literature, and showing gender differences, corroborating previous findings in psychology. This work constitutes a step towards applying social sensing technologies to the real world by designing and implementing a living lab for students of an international hospitality management school.

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Section: Inference Of First Impressionsmentioning

confidence: 99%

Section: Audio Featuresmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Training on the job: behavioral analysis of job interviews in hospitality

Muralidhar

Nguyen

Frauendorfer

et al. 2016

Proceedings of the 18th ACM International Conference on Multimodal Interaction

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show abstract

“…Our work builds upon and extends work on automatic analysis of social interaction in the workplace [19,42], which has shown the potential of inferring negotiation outcomes [15], job interview ratings [13,40], and other constructs (e.g. engagement, friendliness, or excitement) [25,39,47] up to a certain level of performance. We study a dataset consisting of 169 dyadic interactions between a hotel desk receptionist and a client, where receptionists are played by students from an international hospitality management school who practice real-life situations.…”

Section: Introductionmentioning

confidence: 99%

How may I help you? behavior and impressions in hospitality service encounters

Muralidhar

Mast

Gática-Pérez

2017

Proceedings of the 19th ACM International Conference on Multimodal Interaction

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In the service industry, customers often assess quality of service based on the behavior, perceived personality, and other attributes of the front line service employees they interact with. Interpersonal communication during these interactions is key to determine customer satisfaction and perceived service quality. We present a computational framework to automatically infer perceived performance and skill variables of employees interacting with customers in a hotel reception desk setting using nonverbal behavior, studying a dataset of 169 dyadic interactions involving students from a hospitality management school. We also study the connections between impressions of Big-5 personality traits, attractiveness, and performance of receptionists. In regression tasks, our automatic framework achieves R 2 = 0.30 for performance impressions using audio-visual nonverbal cues, compared to 0.35 using personality impressions, while attractiveness impressions had low predictive power. We also study the integration of nonverbal behavior and Big-5 personality impressions towards increasing regression performance (R 2 = 0.37).

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We Are What We Repeatedly Do—But in What Context? The Role of Situational Factors in Assessing Personality via Nonverbal Behavior

Klafehn

Kell

Andrews

et al. 2016

ETS Research Report Series

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While the vast majority of assessments designed to measure noncognitive skills rely heavily on self‐report, concerns surrounding faking and response bias have led to an increased demand for the development of new and innovative methods by which to measure such traits, particularly in high stakes contexts. The focus of this report is to address one such method—the inference of noncognitive skills, namely personality, through nonverbal behavior—and the role contextual factors may play in influencing the validity of conclusions drawn from its application. Specifically, this report discusses the various ways in which characteristics of the task (e.g., level of cooperation, physical effort) may facilitate or hinder the assessment of personality when personality is being inferred through observable behavior. This discussion is dovetailed by a review of research from the nonverbal assessment and interpersonal task literatures, as well as a synthesis of these literatures to highlight the degree to which situational factors (as manifested through different tasks) influence the assessment of personality via nonverbal behavior. Additionally, the potential value of using noninvasive tools, such as the sociometer, to collect nonverbal behavioral data during these tasks is discussed. The report concludes with a brief commentary on the feasibility of using nonverbal methods to assess noncognitive skills, with a specific focus on the extent to which structuring the context to elicit certain behaviors may influence the validity and robustness of nonverbal responses as a measurement source.

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Automated prediction and analysis of job interview performance: The role of what you say and how you say it

Cited by 94 publications

References 19 publications

Training on the job: behavioral analysis of job interviews in hospitality

Training on the job: behavioral analysis of job interviews in hospitality

How may I help you? behavior and impressions in hospitality service encounters

We Are What We Repeatedly Do—But in What Context? The Role of Situational Factors in Assessing Personality via Nonverbal Behavior

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