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op-ed | Modelling melody: Music in the era of Artificial Intelligence and Machine Learning

In the era of Artificial Intelligence and Machine Learning, the day is probably not very far when the new-age ChatGPTs will start creating new ragas, tunes, or pieces of music

France
French
Pierre-roy
Pranita-sarmah
Francois-pachet
Hoom-kare
Vishnu-narayan-bhatkhande
Davidm-franz
Jean-julien-aucouturier
Merriam-webster
Sangeet-paddhati
Nandini-sarma

Recognizing liars from the sound of their voice?

 E-Mail Faster speech rate, greater intensity in the middle of the word, and falling pitch at the end of the word: that is the prosody[1] to adopt if one wants to come across as reliable and honest to one s listeners. Scientists from the Science and Technology for Music and Sound laboratory (CNRS/Ircam/Sorbonne Université/Ministère de la Culture)[2] and the Perceptual Systems Laboratory (CNRS/ENS PSL) have conducted a series of experiments[3] to understand how we decide, based on the voice, whether a speaker is honest and confident, or on the contrary dishonest and uncertain. They have also shown that this signature was perceived similarly in a number of languages (French, English, Spanish), and that it is registered automatically by the brain: even when participants were not judging the speaker s certainty or honesty, this characteristic sound impacted how they memorized the words. Prosody consequently conveys information on the truth-value or certainty of a proposition. Scien

France
Spain
Spanish
French
Louise-goupil
Jean-julien-aucouturier
Alexiane-agullo
Nature-communications
Technology-for-music
University-of-east-london
Perceptual-systems-laboratory
Sorbonne-universit

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