Cross-cultural emotional prosody recognition: Evidence from Chinese and British listeners

This cross-cultural study of emotional tone of voice recognition tests the in-group advantage hypothesis (Elfenbein & Ambady, 2002) employing a quasi-balanced design. Individuals of Chinese and British background were asked to recognise pseudosentences produced by Chinese and British native speakers, displaying one of seven emotions (anger, disgust, fear, happy, neutral tone of voice, sad, and surprise). Findings reveal that emotional displays were recognised at rates higher than predicted by chance; however, members of each cultural group were more accurate in recognising the displays communicated by a member of their own cultural group than a member of the other cultural group. Moreover, the evaluation of error matrices indicates that both culture groups relied on similar mechanism when recognising emotional displays from the voice. Overall, the study reveals evidence for both universal and culture-specific principles in vocal emotion recognition. © 2013 © 2013 Taylor & Francis

dráma 4 felvonásban - írta Eugéne Brieux - fordította Zigány Árpád - rendező Kemény Lajos

Városi Szinház. Debreczen, 1913 február 15 -én szombaton: K. Hegyesy Mari és Beregi Oszkár a budapesti nemzeti szinház művészeinek együttes felléptével.Debreceni Egyetem Egyetemi és Nemzeti Könyvtá

Social power and recognition of emotional prosody: High power is associated with lower recognition accuracy than low power

Listeners have to pay close attention to a speaker’s tone of voice (prosody) during daily conversations. This is particularly important when trying to infer the emotional state of the speaker. While a growing body of research has explored how emotions are processed from speech in general, little is known about how psycho-social factors such as social power can shape the perception of vocal emotional attributes. Thus, the present studies explored how social power affects emotional prosody recognition. In a correlational (Study 1) and an experimental study (Study 2), we show that high power is associated with lower accuracy in emotional prosody recognition than low power. These results, for the first time, suggest that individuals experiencing high or low power perceive emotional language differently

Neurophysiological markers of phrasal verb processing: evidence from L1 and L2 speakers

Bilingual Figurative Language Processing is a timely book that provides a much-needed bilingual perspective to the broad field of figurative language. This is the first book of its kind to address how bilinguals acquire, store, and process figurative language, such as idiomatic expressions (e.g., kick the bucket), metaphors (e.g., lawyers are sharks), and irony, and how these tropes might interact in real time across the bilingual's two languages. This volume offers the reader and the bilingual student an overview of the major strands of research, both theoretical and empirical, currently being undertaken in this field of inquiry. At the same time, Bilingual Figurative Language Processing provides readers and undergraduate and graduate students with the opportunity to acquire hands-on experience in the development of psycholinguistic experiments in bilingual figurative language. Each chapter includes a section on suggested student research projects. Selected chapters provide detailed procedures on how to design and develop psycholinguistic experiments

Towards a Classifier to Recognize Emotions Using Voice to Improve Recommendations

[EN] The recognition of emotions in tone voice is currently a tool with a high potential when it comes to making recommendations, since it allows to personalize recommendations using the mood of the users as information. However, recognizing emotions using tone of voice is a complex task since it is necessary to pre-process the signal and subsequently recognize the emotion. Most of the current proposals use recurrent networks based on sequences with a temporal relationship. The disadvantage of these networks is that they have a high runtime, which makes it difficult to use in real-time applications. On the other hand, when defining this type of classifier, culture and language must be taken into account, since the tone of voice for the same emotion can vary depending on these cultural factors. In this work we propose a culturally adapted model for recognizing emotions from the voice tone using convolutional neural networks. This type of network has a relatively short execution time allowing its use in real time applications. The results we have obtained improve the current state of the art, reaching 93.6% success over the validation set.This work is partially supported by the Spanish Government project TIN2017-89156-R, GVA-CEICE project PROMETEO/2018/002, Generalitat Valenciana and European Social Fund FPI grant ACIF/2017/085, Universitat Politecnica de Valencia research grant (PAID-10-19), and by the Spanish Government (RTI2018-095390-B-C31).Fuentes-López, JM.; Taverner-Aparicio, JJ.; Rincón Arango, JA.; Botti Navarro, VJ. (2020). Towards a Classifier to Recognize Emotions Using Voice to Improve Recommendations. Springer. 218-225. https://doi.org/10.1007/978-3-030-51999-5_18S218225Balakrishnan, A., Rege, A.: Reading emotions from speech using deep neural networks. Technical report, Stanford University, Computer Science Department (2017)Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9, 1735–1780 (1997)Kerkeni, L., Serrestou, Y., Mbarki, M., Raoof, K., Mahjoub, M.: Speech emotion recognition: methods and cases study, pp. 175–182 (2018)McCluskey, K.W., Albas, D.C., Niemi, R.R., Cuevas, C., Ferrer, C.: Cross-cultural differences in the perception of the emotional content of speech: a study of the development of sensitivity in Canadian and Mexican children. Dev. Psychol. 11(5), 551 (1975)Paliwal, K.K.: Spectral subband centroid features for speech recognition. In: Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP 1998 (Cat. No. 98CH36181), vol. 2, pp. 617–620. IEEE (1998)Paulmann, S., Uskul, A.K.: Cross-cultural emotional prosody recognition: evidence from Chinese and British listeners. Cogn. Emot. 28(2), 230–244 (2014)Pépiot, E.: Voice, speech and gender: male-female acoustic differences and cross-language variation in English and French speakers. Corela Cogn. Représent. Lang. (HS-16) (2015)Picard, R.W., et al.: Affective computing. Perceptual Computing Section, Media Laboratory, Massachusetts Institute of Technology (1995)Rincon, J., de la Prieta, F., Zanardini, D., Julian, V., Carrascosa, C.: Influencing over people with a social emotional model. Neurocomputing 231, 47–54 (2017)Russell, J.A., Lewicka, M., Niit, T.: A cross-cultural study of a circumplex model of affect. J. Pers. Soc. Psychol. 57(5), 848 (1989)Schuller, B., Rigoll, G., Lang, M.: Hidden Markov model-based speech emotion recognition, vol. 2, pp. 401–404 (2003)Schuller, B., Villar, R., Rigoll, G., Lang, M.: Meta-classifiers in acoustic and linguistic feature fusion-based affect recognition, vol. 1, pp. 325–328 (2005)Thompson, W., Balkwill, L.-L.: Decoding speech prosody in five languages. Semiotica 2006, 407–424 (2006)Tyagi, V., Wellekens, C.: On desensitizing the Mel-cepstrum to spurious spectral components for robust speech recognition. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP 2005, vol. 1, pp. I–529. IEEE (2005)Ueda, M., Morishita, Y., Nakamura, T., Takata, N., Nakajima, S.: A recipe recommendation system that considers user’s mood. In: Proceedings of the 18th International Conference on Information Integration and Web-based Applications and Services, pp. 472–476. ACM (2016)Zhang, B., Quan, C., Ren, F.: Study on CNN in the recognition of emotion in audio and images. In: 2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS), pp. 1–5, June 201

Emotional Speech Perception Unfolding in Time: The Role of the Basal Ganglia

The basal ganglia (BG) have repeatedly been linked to emotional speech processing in studies involving patients with neurodegenerative and structural changes of the BG. However, the majority of previous studies did not consider that (i) emotional speech processing entails multiple processing steps, and the possibility that (ii) the BG may engage in one rather than the other of these processing steps. In the present study we investigate three different stages of emotional speech processing (emotional salience detection, meaning-related processing, and identification) in the same patient group to verify whether lesions to the BG affect these stages in a qualitatively different manner. Specifically, we explore early implicit emotional speech processing (probe verification) in an ERP experiment followed by an explicit behavioral emotional recognition task. In both experiments, participants listened to emotional sentences expressing one of four emotions (anger, fear, disgust, happiness) or neutral sentences. In line with previous evidence patients and healthy controls show differentiation of emotional and neutral sentences in the P200 component (emotional salience detection) and a following negative-going brain wave (meaning-related processing). However, the behavioral recognition (identification stage) of emotional sentences was impaired in BG patients, but not in healthy controls. The current data provide further support that the BG are involved in late, explicit rather than early emotional speech processing stages

Histaminylation of glutamine residues is a novel posttranslational modification implicated in G-protein signaling

Posttranslational modifications (PTM) have been shown to be essential for protein function and signaling. Here we report the identification of a novel modification, protein transfer of histamine, and provide evidence for its function in G protein signaling. Histamine, known as neurotransmitter and mediator of the inflammatory response, was found incorporated into mastocytoma proteins. Histaminylation was dependent on transglutaminase II. Mass spectrometry confirmed histamine modification of the small and heterotrimeric G proteins Cdc42, Galphao1 and Galphaq. The modification was specific for glutamine residues in the catalytic core, and triggered their constitutive activation. TGM2-mediated histaminylation is thus a novel PTM that functions in G protein signaling. Protein alphamonoaminylations, thus including histaminylation, serotonylation, dopaminylation and norepinephrinylation, hence emerge as a novel class of regulatory PTMs

Preferential decoding of emotion from human non-linguistic vocalizations versus speech prosody

This study used event-related brain potentials (ERPs) to compare the time course of emotion processing from non-linguistic vocalizations versus speech prosody, to test whether vocalizations are treated preferentially by the neurocognitive system. Participants passively listened to vocalizations or pseudo-utterances conveying anger, sadness, or happiness as the EEG was recorded. Simultaneous effects of vocal expression type and emotion were analyzed for three ERP components (N100, P200, late positive component). Emotional vocalizations and speech were differentiated very early (N100) and vocalizations elicited stronger, earlier, and more differentiated P200 responses than speech. At later stages (450–700 ms), anger vocalizations evoked a stronger late positivity (LPC) than other vocal expressions, which was similar but delayed for angry speech. Individuals with high trait anxiety exhibited early, heightened sensitivity to vocal emotions (particularly vocalizations). These data provide new neurophysiological evidence that vocalizations, as evolutionarily primitive signals, are accorded precedence over speech-embedded emotions in the human voice

Recognizing Emotions in a Foreign Language

Expressions of basic emotions (joy, sadness, anger, fear, disgust) can be recognized pan-culturally from the face and it is assumed that these emotions can be recognized from a speaker's voice, regardless of an individual's culture or linguistic ability. Here, we compared how monolingual speakers of Argentine Spanish recognize basic emotions from pseudo-utterances ("nonsense speech") produced in their native language and in three foreign languages (English, German, Arabic). Results indicated that vocal expressions of basic emotions could be decoded in each language condition at accuracy levels exceeding chance, although Spanish listeners performed significantly better overall in their native language ("in-group advantage"). Our findings argue that the ability to understand vocally-expressed emotions in speech is partly independent of linguistic ability and involves universal principles, although this ability is also shaped by linguistic and cultural variables

Seeing Emotion with Your Ears: Emotional Prosody Implicitly Guides Visual Attention to Faces

Interpersonal communication involves the processing of multimodal emotional cues, particularly facial expressions (visual modality) and emotional speech prosody (auditory modality) which can interact during information processing. Here, we investigated whether the implicit processing of emotional prosody systematically influences gaze behavior to facial expressions of emotion. We analyzed the eye movements of 31 participants as they scanned a visual array of four emotional faces portraying fear, anger, happiness, and neutrality, while listening to an emotionally-inflected pseudo-utterance (Someone migged the pazing) uttered in a congruent or incongruent tone. Participants heard the emotional utterance during the first 1250 milliseconds of a five-second visual array and then performed an immediate recall decision about the face they had just seen. The frequency and duration of first saccades and of total looks in three temporal windows ([0–1250 ms], [1250–2500 ms], [2500–5000 ms]) were analyzed according to the emotional content of faces and voices. Results showed that participants looked longer and more frequently at faces that matched the prosody in all three time windows (emotion congruency effect), although this effect was often emotion-specific (with greatest effects for fear). Effects of prosody on visual attention to faces persisted over time and could be detected long after the auditory information was no longer present. These data imply that emotional prosody is processed automatically during communication and that these cues play a critical role in how humans respond to related visual cues in the environment, such as facial expressions