Emergence of linguistic laws in human voice
| Autor: | Iván González Torre, Jordi Luque, Bartolo Luque, Lucas Lacasa, Antoni Hernández-Fernández |
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| Přispěvatelé: | Universitat Politècnica de Catalunya. Institut de Ciències de l'Educació, Universitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge |
| Rok vydání: | 2017 |
| Předmět: |
FOS: Computer and information sciences
0301 basic medicine Physics - Physics and Society Computer science Informàtica::Sistemes d'informació [Àrees temàtiques de la UPC] FOS: Physical sciences Reconeixement automàtic de la parla Physics and Society (physics.soc-ph) computer.software_genre 01 natural sciences Article Human Voice 03 medical and health sciences Zipf's Law Transcription (linguistics) 0103 physical sciences Animals Humans Speech 010306 general physics Human communication Human voice Language Linguistic Laws Computer Science - Computation and Language Brevity Law Gutenberg-Richter Law Multidisciplinary business.industry Communication Communication Systems Automatic speech recognition Heaps Law Linguistics Models Theoretical Linguistic analysis (Linguistics) Animal Communication 030104 developmental biology Law Voice Anàlisi lingüística Artificial intelligence Informàtica::Intel·ligència artificial::Llenguatge natural [Àrees temàtiques de la UPC] business Computation and Language (cs.CL) computer Algorithms Natural language processing |
| Zdroj: | Recercat. Dipósit de la Recerca de Catalunya instname Scientific Reports UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| ISSN: | 2045-2322 |
| DOI: | 10.1038/srep43862 |
| Popis: | Linguistic laws constitute one of the quantitative cornerstones of modern cognitive sciences and have been routinely investigated in written corpora, or in the equivalent transcription of oral corpora. This means that inferences of statistical patterns of language in acoustics are biased by the arbitrary, language-dependent segmentation of the signal, and virtually precludes the possibility of making comparative studies between human voice and other animal communication systems. Here we bridge this gap by proposing a method that allows to measure such patterns in acoustic signals of arbitrary origin, without needs to have access to the language corpus underneath. The method has been applied to six different human languages, recovering successfully some well-known laws of human communication at timescales even below the phoneme and finding yet another link between complexity and criticality in a biological system. These methods further pave the way for new comparative studies in animal communication or the analysis of signals of unknown code. Comment: Submitted for publication |
| Databáze: | OpenAIRE |
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