@Article{Toro2005,
  author   = {Juan M Toro and Josep B Trobal\'{o}n},
  journal  = {Percept Psychophys},
  title    = {Statistical computations over a speech stream in a rodent.},
  year     = {2005},
  number   = {5},
  pages    = {867-75},
  volume   = {67},
  abstract = {Statistical learning is one of the key mechanisms available to human
	infants and adults when they face the problems of segmenting a speech
	stream (Saffran, Aslin, & Newport, 1996) and extracting long-distance
	regularities (G6mez, 2002; Pe\~na, Bonatti, Nespor, & Mehler, 2002).
	In the present study, we explore statistical learning abilities in
	rats in the context of speech segmentation experiments. In a series
	of five experiments, we address whether rats can compute the necessary
	statistics to be able to segment synthesized speech streams and detect
	regularities associated with grammatical structures. Our results
	demonstrate that rats can segment the streams using the frequency
	of co-occurrence (not transitional probabilities, as human infants
	do) among items, showing that some basic statistical learning mechanism
	generalizes over nonprimate species. Nevertheless, rats did not differentiate
	among test items when the stream was organized over more complex
	regularities that involved nonadjacent elements and abstract grammar-like
	rules.},
  keywords = {Animals, Learning, Long-Evans, Male, Non-U.S. Gov't, Psychophysics, Rats, Research Support, Speech Perception, Vocabulary, 16334058},
}

{"_id":"JeLbw6g63S4iHpu9H","bibbaseid":"toro-trobaln-statisticalcomputationsoveraspeechstreaminarodent-2005","author_short":["Toro, J. M","Trobalón, J. B"],"bibdata":{"bibtype":"article","type":"article","author":[{"firstnames":["Juan","M"],"propositions":[],"lastnames":["Toro"],"suffixes":[]},{"firstnames":["Josep","B"],"propositions":[],"lastnames":["Trobalón"],"suffixes":[]}],"journal":"Percept Psychophys","title":"Statistical computations over a speech stream in a rodent.","year":"2005","number":"5","pages":"867-75","volume":"67","abstract":"Statistical learning is one of the key mechanisms available to human infants and adults when they face the problems of segmenting a speech stream (Saffran, Aslin, & Newport, 1996) and extracting long-distance regularities (G6mez, 2002; Peña, Bonatti, Nespor, & Mehler, 2002). In the present study, we explore statistical learning abilities in rats in the context of speech segmentation experiments. In a series of five experiments, we address whether rats can compute the necessary statistics to be able to segment synthesized speech streams and detect regularities associated with grammatical structures. Our results demonstrate that rats can segment the streams using the frequency of co-occurrence (not transitional probabilities, as human infants do) among items, showing that some basic statistical learning mechanism generalizes over nonprimate species. Nevertheless, rats did not differentiate among test items when the stream was organized over more complex regularities that involved nonadjacent elements and abstract grammar-like rules.","keywords":"Animals, Learning, Long-Evans, Male, Non-U.S. Gov't, Psychophysics, Rats, Research Support, Speech Perception, Vocabulary, 16334058","bibtex":"@Article{Toro2005,\n author = {Juan M Toro and Josep B Trobal\\'{o}n},\n journal = {Percept Psychophys},\n title = {Statistical computations over a speech stream in a rodent.},\n year = {2005},\n number = {5},\n pages = {867-75},\n volume = {67},\n abstract = {Statistical learning is one of the key mechanisms available to human\n\tinfants and adults when they face the problems of segmenting a speech\n\tstream (Saffran, Aslin, & Newport, 1996) and extracting long-distance\n\tregularities (G6mez, 2002; Pe\\~na, Bonatti, Nespor, & Mehler, 2002).\n\tIn the present study, we explore statistical learning abilities in\n\trats in the context of speech segmentation experiments. In a series\n\tof five experiments, we address whether rats can compute the necessary\n\tstatistics to be able to segment synthesized speech streams and detect\n\tregularities associated with grammatical structures. Our results\n\tdemonstrate that rats can segment the streams using the frequency\n\tof co-occurrence (not transitional probabilities, as human infants\n\tdo) among items, showing that some basic statistical learning mechanism\n\tgeneralizes over nonprimate species. Nevertheless, rats did not differentiate\n\tamong test items when the stream was organized over more complex\n\tregularities that involved nonadjacent elements and abstract grammar-like\n\trules.},\n keywords = {Animals, Learning, Long-Evans, Male, Non-U.S. Gov't, Psychophysics, Rats, Research Support, Speech Perception, Vocabulary, 16334058},\n}\n\n","author_short":["Toro, J. M","Trobalón, J. B"],"key":"Toro2005","id":"Toro2005","bibbaseid":"toro-trobaln-statisticalcomputationsoveraspeechstreaminarodent-2005","role":"author","urls":{},"keyword":["Animals","Learning","Long-Evans","Male","Non-U.S. Gov't","Psychophysics","Rats","Research Support","Speech Perception","Vocabulary","16334058"],"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://endress.org/publications/ansgar.bib","dataSources":["xPGxHAeh3vZpx4yyE","TXa55dQbNoWnaGmMq"],"keywords":["animals","learning","long-evans","male","non-u.s. gov't","psychophysics","rats","research support","speech perception","vocabulary","16334058"],"search_terms":["statistical","computations","over","speech","stream","rodent","toro","trobalón"],"title":"Statistical computations over a speech stream in a rodent.","year":2005}