The sound of sarcasm
نویسندگان
چکیده
The present study was conducted to identify possible acoustic cues of sarcasm. Native English speakers produced a variety of simple utterances to convey four different attitudes: sarcasm, humour, sincerity, and neutrality. Following validation by a separate naı̈ve group of native English speakers, the recorded speech was subjected to acoustic analyses for the following features: mean fundamental frequency (F0), F0 standard deviation, F0 range, mean amplitude, amplitude range, speech rate, harmonics-to-noise ratio (HNR, to probe for voice quality changes), and one-third octave spectral values (to probe resonance changes). The results of analyses indicated that sarcasm was reliably characterized by a number of prosodic cues, although one acoustic feature appeared particularly robust in sarcastic utterances: overall reductions in mean F0 relative to all other target attitudes. Sarcasm was also reliably distinguished from sincerity by overall reductions in HNR and in F0 standard deviation. In certain linguistic contexts, sarcasm could be differentiated from sincerity and humour through changes in resonance and reductions in both speech rate and F0 range. Results also suggested a role of language used by speakers in conveying sarcasm and sincerity. It was concluded that sarcasm in speech can be characterized by a specific pattern of prosodic cues in addition to textual cues, and that these acoustic characteristics can be influenced by language used by the speaker. 2007 Elsevier B.V. All rights reserved.
منابع مشابه
Approaches for Computational Sarcasm Detection: A Survey
Sentiment Analysis deals not only with the positive and negative sentiment detection in the text but it also considers the prevalence and challenges of sarcasm in sentiment-bearing text. Automatic Sarcasm detection deals with the detection of sarcasm in text. In the recent years, work in sarcasm detection gains popularity and has wide applicability in sentiment analysis. This paper complies the...
متن کاملSarcasm Suite: A Browser-Based Engine for Sarcasm Detection and Generation
Sarcasm Suite is a browser-based engine that deploys five of our past papers in sarcasm detection and generation. The sarcasm detection modules use four kinds of incongruity: sentiment incongruity, semantic incongruity, historical context incongruity and conversational context incongruity. The sarcasm generation module is a chatbot that responds sarcastically to user input. With a visually appe...
متن کاملHow Challenging is Sarcasm versus Irony Classification?: An Analysis From Human and Computational Perspectives
Sarcasm and irony, although similar, differ in that sarcasm has an impact on sentiment (because it is used to ridicule a target) while irony does not. Past work treats the two interchangeably. In this paper, we wish to validate if sarcasm versus irony classification is indeed a challenging task. To this end, we use a dataset of quotes from English literature, and conduct experiments from two pe...
متن کامل"Having 2 hours to write a paper is fun!": Detecting Sarcasm in Numerical Portions of Text
Sarcasm occurring due to the presence of numerical portions in text has been quoted as an error made by automatic sarcasm detection approaches in the past. We present a first study in detecting sarcasm in numbers, as in the case of the sentence ‘Love waking up at 4 am’. We analyze the challenges of the problem, and present Rulebased, Machine Learning and Deep Learning approaches to detect sarca...
متن کاملFathoming the Cultural Schema of Ta’ne in Persian Language: A Cultural Linguistic Study
The aim of the present article is to probe the functions of the cultural schema of Ta’ne (sarcasm) in Persian. Results from 100 recorded instantiations of Ta’ne accumulated through ethnographic approach indicated that it served different functions including complaint, criticism, insult, contempt, humor, and compliment. The results were then discussed with reference to the cultural differences i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Speech Communication
دوره 50 شماره
صفحات -
تاریخ انتشار 2008