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      Handbook of Artificial Intelligence for Music : Foundations, Advanced Approaches, and Developments for Creativity 

      Structure, Abstraction and Reference in Artificial Musical Intelligence

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      Springer International Publishing

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          Music, language and meaning: brain signatures of semantic processing.

          Semantics is a key feature of language, but whether or not music can activate brain mechanisms related to the processing of semantic meaning is not known. We compared processing of semantic meaning in language and music, investigating the semantic priming effect as indexed by behavioral measures and by the N400 component of the event-related brain potential (ERP) measured by electroencephalography (EEG). Human subjects were presented visually with target words after hearing either a spoken sentence or a musical excerpt. Target words that were semantically unrelated to prime sentences elicited a larger N400 than did target words that were preceded by semantically related sentences. In addition, target words that were preceded by semantically unrelated musical primes showed a similar N400 effect, as compared to target words preceded by related musical primes. The N400 priming effect did not differ between language and music with respect to time course, strength or neural generators. Our results indicate that both music and language can prime the meaning of a word, and that music can, as language, determine physiological indices of semantic processing.
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            Probabilistic models of expectation violation predict psychophysiological emotional responses to live concert music.

            We present the results of a study testing the often-theorized role of musical expectations in inducing listeners' emotions in a live flute concert experiment with 50 participants. Using an audience response system developed for this purpose, we measured subjective experience and peripheral psychophysiological changes continuously. To confirm the existence of the link between expectation and emotion, we used a threefold approach. (1) On the basis of an information-theoretic cognitive model, melodic pitch expectations were predicted by analyzing the musical stimuli used (six pieces of solo flute music). (2) A continuous rating scale was used by half of the audience to measure their experience of unexpectedness toward the music heard. (3) Emotional reactions were measured using a multicomponent approach: subjective feeling (valence and arousal rated continuously by the other half of the audience members), expressive behavior (facial EMG), and peripheral arousal (the latter two being measured in all 50 participants). Results confirmed the predicted relationship between high-information-content musical events, the violation of musical expectations (in corresponding ratings), and emotional reactions (psychologically and physiologically). Musical structures leading to expectation reactions were manifested in emotional reactions at different emotion component levels (increases in subjective arousal and autonomic nervous system activations). These results emphasize the role of musical structure in emotion induction, leading to a further understanding of the frequently experienced emotional effects of music.
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              Multiple viewpoint systems for music prediction

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                Author and book information

                Book Chapter
                2021
                July 03 2021
                : 409-422
                10.1007/978-3-030-72116-9_15
                3c85d106-766b-4d6f-96cb-446c6e7f2785
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