Emotional responses to Hindustani raga music: the role of musical structure

In Indian classical music, ragas constitute specific combinations of tonic intervals potentially capable of evoking distinct emotions. A raga composition is typically presented in two modes, namely, alaap and gat. Alaap is the note by note delineation of a raga bound by a slow tempo, but not bound by a rhythmic cycle. Gat on the other hand is rendered at a faster tempo and follows a rhythmic cycle. Our primary objective was to (1) discriminate the emotions experienced across alaap and gat of ragas, (2) investigate the association of tonic intervals, tempo and rhythmic regularity with emotional response. 122 participants rated their experienced emotion across alaap and gat of 12 ragas. Analysis of the emotional responses revealed that (1) ragas elicit distinct emotions across the two presentation modes, and (2) specific tonic intervals are robust predictors of emotional response. Specifically, our results showed that the ‘minor second’ is a direct predictor of negative valence. (3) Tonality determines the emotion experienced for a raga where as rhythmic regularity and tempo modulate levels of arousal. Our findings provide new insights into the emotional response to Indian ragas and the impact of tempo, rhythmic regularity and tonality on it.

How does the brain mediate interpretation of incongruent auditory emotions? The neural response to prosody in the presence of conflicting lexico-semantic cues

We frequently encounter conflicting emotion cues. This study examined how the neural response to emotional prosody differed in the presence of congruent and incongruent lexico-semantic cues. Two hypotheses were assessed: (i) decoding emotional prosody with conflicting lexico-semantic cues would activate brain regions associated with cognitive conflict (anterior cingulate and dorsolateral prefrontal cortex) or (ii) the increased attentional load of incongruent cues would modulate the activity of regions that decode emotional prosody (right lateral temporal cortex). While the participants indicated the emotion conveyed by prosody, functional magnetic resonance imaging data were acquired on a 3T scanner using blood oxygenation level-dependent contrast. Using SPM5, the response to congruent cues was contrasted with that to emotional prosody alone, as was the response to incongruent lexico-semantic cues (for the 'cognitive conflict' hypothesis). The right lateral temporal lobe region of interest analyses examined modulation of activity in this brain region between these two contrasts (for the 'prosody cortex' hypothesis). Dorsolateral prefrontal and anterior cingulate cortex activity was not observed, and neither was attentional modulation of activity in right lateral temporal cortex activity. However, decoding emotional prosody with incongruent lexico-semantic cues was strongly associated with left inferior frontal gyrus activity. This specialist form of conflict is therefore not processed by the brain using the same neural resources as non-affective cognitive conflict and neither can it be handled by associated sensory cortex alone. The recruitment of inferior frontal cortex may indicate increased semantic processing demands but other contributory functions of this region should be explored.

Chatterbox challenge as a test-bed for synthetic emotions

Chatterbox Challenge is an annual web-based contest for artificial conversational systems, ACE. The 2010 instantiation was the tenth consecutive contest held between March and June in the 60th year following the publication of Alan Turing’s influential disquisition ‘computing machinery and intelligence’. Loosely based on Turing’s viva voca interrogator-hidden witness imitation game, a thought experiment to ascertain a machine’s capacity to respond satisfactorily to unrestricted questions, the contest provides a platform for technology comparison and evaluation. This paper provides an insight into emotion content in the entries since the 2005 Chatterbox Challenge. The authors find that synthetic textual systems, none of which are backed by academic or industry funding, are, on the whole and more than half a century since Weizenbaum’s natural language understanding experiment, little further than Eliza in terms of expressing emotion in dialogue. This may be a failure on the part of the academic AI community for ignoring the Turing test as an engineering challenge.

The world of emotions is not two-dimensional

For more than half a century, emotion researchers have attempted to establish the dimensional space that most economically accounts for similarities and differences in emotional experience. Today, many researchers focus exclusively on two-dimensional models involving valence and arousal. Adopting a theoretically based approach, we show for three languages that four dimensions are needed to satisfactorily represent similarities and differences in the meaning of emotion words. In order of importance, these dimensions are evaluation-pleasantness, potency-control, activation-arousal, and unpredictability. They were identified on the basis of the applicability of 144 features representing the six components of emotions: (a) appraisals of events, (b) psychophysiological changes, (c) motor expressions, (d) action tendencies, (e) subjective experiences, and (f) emotion regulation.