Ce diaporama a bien été signalé.
Le téléchargement de votre SlideShare est en cours. ×

word meaning.ppsx

Prochain SlideShare
Chargement dans…3

Consultez-les par la suite

1 sur 43 Publicité

Plus De Contenu Connexe

Similaire à word meaning.ppsx (20)

Plus récents (20)


word meaning.ppsx

  1. 1. The Psychology of Language Trevor A. Harley
  2. 2. Out line Introduction Classic approaches to semantics Semantic Networks Semantic Features Family Resemblance Models Combining Concepts Figurative Language The neuroscience of semantics Connectionist approaches to semantics 2
  3. 3. Hello! I am Ata Mohammed Saeed I am here because I love to give presentations. You can find me at atta.saeed@gmail.com 3
  4. 4. Introduction How do we represent the meaning of words? How do we organize our knowledge of the world? Word meaning, examines issues involved in the study of semantics, in particular how we represent the meanings of individual words. Categorization, associations between words, use of metaphor and idiom, and connectionist modeling of semantics are among the topics addressed.
  5. 5. First, we can translate words from one language to another, even though not every word meaning is represented by a simple, single word in every language. Second, there is an imperfect mapping between words and their meanings such that some words have more than one meaning (ambiguity), while some words have the same meaning as each other (synonymy). Third, the meaning of words depends to some extent on the context. Hence a big ant is very different in size from a big elephant, and the red in “the red sunset” is a different color from “she blushed and turned red.” 5 (Hirsh-Pasek, Reeves, & Golinkoff, 1993)
  6. 6. Tulving (1972) distinguished between episodic and semantic memory.  Episodic memory is our memory for events and particular episodes;  semantic memory is, in simple terms, our general knowledge. my knowledge that the capital of France is Paris is stored in semantic memory, while my memory of a trip to Paris is an instance of an episodic memory. • More example: Semantic or Episodic? - dogs can’t fly. - when you last rode a bike - Christmas is on the 25th f December. 6
  7. 7. Big concept  The notion of meaning is closely bound to that of categorization.  A concept determines how things are related or categorized. It is a mental representation of a category.  It enables us to group things together, so that instances of a category all have something in common. Thus concepts somehow specify category membership.  All words have an underlying concept, but not all concepts are labeled by a word. For example, we do not have a special word for brown dogs. In English we have a word “dog” that we can use about certain things in the world, but not about others. In principle we could have a word, say “brog,” to refer to brown dogs. We do not have such a term, probably because it is not a particularly useful one. 7
  8. 8. Cont…  Semantics concerns more than associations .  Words can be related in meaning without being associated (e.g., “yacht” and “ship”), so any theory of word meaning cannot rely simply on word association.  Words with similar meanings tend to occur in similar contexts.  Lund, Burgess, and Atchley (1995) showed that semantically similar words (e.g., “bed” and “table”) are interchangeable within a sentence; the resulting sentence, while maybe pragmatically implausible, nevertheless makes sense. - The child slept on the bed. - The child slept on the table. - The child slept in the cradle. - *The child slept in the baby. 8
  9. 9. The denotation of a word is its core, essential meaning. Classic approaches to semantics The connotations of a word are all of its secondary implications, or emotional or evaluative associations. 9 For example, the denotation of the word “dog” is its core meaning: it is the relation between the word and the class of objects to which it can refer. The connotations of “dog” might be “nice,” “frightening,” or “smelly.” Put another way, people agree on the denotation, but the connotations differ from person to person.
  10. 10. Consider the words “Hesperus” (Greek for “The Evening Star”) and “Phosphorus” (Greek for “The Morning Star”). They have the same referent in our universe, namely the planet Venus, but they have different senses. The ancients did not know that Hesperus and Phosphorus were the same thing, so even though the words actually refer to the same thing (the planet Venus), the words have different senses (Johnson- Laird, 1983). The sense of “Hesperus” is the planet you can see in the evening sky, but the sense of “Phosphorus” is the one in the morning sky. 10
  11. 11. Semantic Network  One of the most influential of all processing approaches to meaning is based on the idea that the meaning of a word is given by how it is embedded within a network of other meanings.  Some of the earliest theories of meaning, from those of Aristotle to those of the behaviorists, viewed meaning as deriving from a word’s association.  From infancy, we are exposed to many episodes involving the word “dog.” For the behaviorists, the meaning of the word “dog” was simply the sum of all our associations to the word: It obtains its meaning by its place in a network of associations.  The meaning of “dog” might involve an association with “barks,” “four legs,” “furry,” and so on.  It soon became apparent that association in itself was insufficiently powerful to be able to capture all aspects of meaning.  There is no structure in an associative network, with no relation between words, no hierarchy of information, and no cognitive economy. 11
  12. 12. The Collins and Quillian senanic network model A semantic network is particularly useful for representing information about natural kind terms. These are words that denote naturally occurring categories and their members—such as types of animal, or metal, or precious stone. The scheme attributes fundamental importance to their inherently hierarchical nature: For example, a bald eagle is a type of eagle, an eagle is a type of bird of prey, a bird of prey is a bird, and a bird is a type of animal. 12
  13. 13. Example of a hierarchical semantic network (based on Collins & Quillian, 1969) 13
  14. 14. The sentence verification task 14
  15. 15. The sentence verification task One of the most commonly used tasks in early semantic memory research was sentence verification. Participants are presented with simple “facts” and have to press one button if the sentence is true, another if it is false. The reaction time is an index of how difficult the decision was. Collins and Quillian (1969) presented participants with sentences such as: - A robin is a robin. - A robin is a bird. - A robin is an animal. - A robin is a fish. 15
  16. 16. Problems with the Collins and Quillian mode First, clearly not all information is easily represented in hierarchical form. What is the relation between “truth,” “justice,” and “law,” for example? Second problem is that the materials in the sentence verification task that appear to support the hierarchical model confound semantic distance with what is called conjoint frequency. Such as The words “bird” and “robin”. Conjoint frequency is a measure of how frequently two words co-occur. When you control for conjoint frequency, the linear relation between semantic distance and time is weakened (Conrad, 1972; Wilkins, 1971). Third, the hierarchical model makes some incorrect predictions. For example: - A cow is an animal. - A cow is a mammal. 16
  17. 17. Revisions to the semantic network model Collins and Loftus (1975) proposed a revision of the model based on the idea of spreading activation. The structure of the network became more complex, with the links between nodes varying in strength or distance. (Example of a spreading activation semantic network. It should be noted that two dimensions cannot do justice to the necessary complexity of the network. Based on Collins and Loftus (1975).) 17
  18. 18. Semantic features  The Semantic Features are 'categories' that allow us to classify the meaning of a word.  Semantic features work very well in some simple domains where there is a clear relation between the terms.  We can take the idea of semantic features further, and represent the meanings of all words in terms of combinations of as few semantic features as possible  They are usually represented with a headword and using the symbols "+' and' to say if the word contains that feature.  There is no list of semantic features. We need the context to create one. 18
  19. 19. feature Father Mother Daughter Son Human + + + + Older + + - - Female - + + - 19 Semantic features work very well in some simple domains where there is a clear relation between the terms. They are usually represented with a headword and using the symbols "+' and' to say if the word contains that feature. One such domain, much studied by anthropologists, is that of kinship terms. A simple example is shown in the Table: (Decomposition of kinship terms)
  20. 20. Early decompositional theories Katz and Fodor (1963) showed how the meanings of sentences could be derived by combining the semantic features of each individual word in the sentence. It emphasized how we understand ambiguous words. For example: - The witches played around on the beach and kicked the ball. - The witches put on their party frocks and went to the ball. - ? The rock kicked the ball. 20
  21. 21. Feature-list theories and sentence verification Rips et al. (1973) proposed that there are two types of semantic feature. Defining features are essential to the underlying meaning of a word, and relate to properties that things must have to be a member of that category . (for example, a bird is living, it is feathered, lays eggs, and so forth). Characteristic features are usually true of instances of a category, but are not necessarily true (for example, most birds can fly, but penguins and ostriches cannot). According to Rips et al., sentence verification involves making comparisons of the feature lists representing the meaning of the words involved in two stages. For this reason this particular approach is called the feature-comparison theory. 21
  22. 22. Evaluation of decompositional theories Hollan (1975) argued that it is impossible to devise an experiment to distinguish between feature-list and semantic network theories because they are formally equivalent, in that it is impossible to find a prediction that will distinguish between them . Hence for all intents and purposes we can consider network models to be a type of decompositional model. decompositional theories have an intuitive appeal, and they make explicit how we make inferences based on the meaning of words in the sentence verification task. it is difficult to construct decompositional representations for even some of the most common words. Some categories do not have any obvious defining features that are common to all their members. For example “ Game” 22
  23. 23. there are two important issues (McNamara & Miller, 1989):  The first is whether we represent the meanings of words in terms of features.  The other is whether we make use of those features in comprehension. when we see a word like “bachelor,” is the meaning of the unmarried man sense of “bachelor” must clearly contain features that correspond to (+unmarried, +man), although these in turn might summarize decomposition into yet more primitive features. 23 Is semantic decomposition obligatory?
  24. 24. Family resemblance models Many categories seem to be defined by a family resemblance between their members rather than the specification of defining features that all members must possess. 24
  25. 25. Prototype theories A prototype is an average family member (Rosch, 1978). Potential members of the category are identified by how closely they resemble the prototype or category average. The prototype is the “best example” of a concept, and is often a non-existent, composite example. For example, a blackbird (or alternatively, American robin) is very close to being a prototypical bird; it is of average size, has wings and feathers, can fly, and has average features in every respect. A prototype is a special type of schema. A schema is a frame for organizing knowledge that can be structured as a series of slots plus fillers. A prototype is a schema with all the slots filled in with average values. For example, the schema for “bird” comprises a series of slots such as “can fly?” (“yes” for blackbird and robin, “no” for penguin and emu), “bill length” (“short” for robin, “long” for curlew), and “leg Length” (“short” for robin, “long” for stork). 25
  26. 26. Basic levels Rosch (1978) argued that a compromise between cognitive economy and maximum informativeness results in a basic level of categorization that tends to be the default level at which we categorize and think, unless there is particular reason to do otherwise. we use the basic level of “chairs,” rather than the lower level of “armchairs” or the higher level of “furniture.” there is a basic level of categorization that is particularly psychologically salient (Rosch et al., 1976). Rosch et al. (1976) showed that basic levels have a number of advantages over other categories. Participants can easily list most of the attributes of the basic level; it is the level of description most likely to be spontaneously used by adults; sentence verification time is faster for basic-level terms; and children typically acquire the basic level first. 26
  27. 27. Problems with the prototype model Hampton (1981) pointed out that not all types of concepts appear to have prototypes: Abstract concepts in particular are difficult to fit into this scheme. What does it mean, for example, to talk about the prototype for “truth”? The prototype model does not explain why categories cohere. Lakoff (1987) points to some examples of very complex concepts for which it is far from obvious how there could be a prototype—the Australian Aboriginal language Dyirbal has a coherent category of “women, fire, and dangerous things” marked by the word “balan.” 27
  28. 28. Instance theories We make semantic judgments by comparison with specific stored instances. This is the instance approach (Komatsu, 1992), also called the exemplar theory. There are different varieties of the instance approach, depending on how many instances are stored, and on the quality of these instances. The instance approach provides greater informational richness at the expense of cognitive economy. It is quite difficult to distinguish between prototype and instance-based theories. Many of the phenomena explained by prototype theories can also be accounted for by instance-based theories. 28
  29. 29. COMBINING CONCEPTS Wisniewski and Love (1998) showed that in certain circumstances people prefer to comprehend noun combinations on the basis of property relations. High similarity between the constituents of a combination facilitates the production of property relations. People then look for a critical difference between them that can act as the basis of the interpretation. For example, consider “zebra horse.” “Zebra” and “horse” are close in meaning, and the critical difference “has stripes” can easily be used to generate the property relation “a horse with stripes.” 29
  30. 30. FIGURATIVE LANGUAGE Humans make extensive use of non-literal or figurative language. In this we go beyond the Literal meanings of the words involved, for humor, effect, politeness, to play, to be creative—and for a mixture of these and other reasons. Metaphor: is one of the main types of figurative language. It is a special type of conceptual combination, where we combine two concepts that are not normally thought of as being related for some special effect. There are many types of metaphor, depending on the relation between the words actually used and the intended meaning. Here are a few examples: - Vlad fought like a tiger. (Simile) - Vlad exploded with fury. (Strict metaphor) - All hands on deck. (Synecdoche) 30
  31. 31. Idiom: is also one of the main types of figurative language. It can be thought of as frozen metaphors. Whereas we make metaphors up as we go along, idioms have a fixed form and are in general use. The meaning of an idiom is usually quite unrelated to the meaning of its component words. Examples include “to kick the bucket” and “fly off the handle.” Gibbs (1980), using reading times, found that participants take less time to comprehend conventional uses of idioms than unconventional, literal uses, suggesting that people analyze the idiomatic senses of expressions before deriving the literal, unconventional interpretation. Swinney and Cutler (1979) also found that people are as fast to understand familiar idioms as they are comparable phrases used non-idiomatically. They suggested that people store idioms like single lexical items. 31
  32. 32. THE NEUROSCIENCE OF SEMANTICS Shallice (1988; see also Warrington & Cipolotti, 1996, and Warrington & Shallice, 1979) discussed five criteria that could distinguish problems associated with the loss of a representation from problems of accessing it. First, performance should be consistent across trials. If an item is permanently lost, it should never be possible to access it. If an item is available on some trials rather than on others, the difficulty must be one of access. 32
  33. 33. Second, for both degraded stores and access disorders, it should be easier to obtain the superordinate category than to name the item, because that information is very strongly represented; but once the superordinate is obtained, it will be very difficult to obtain any further information in a degraded store. Warrington (1975) found that superordinate information (e.g., that a lion is an animal) may be preserved when more specific information is lost. She proposed that the destruction of semantic memory occurs hierarchically, with lower levels storing specific information being lost before higher levels storing more general information. 33
  34. 34. Third, low-frequency items should be lost first. Low-frequency items should be more susceptible to loss, whereas problems of access should affect all levels equally. Fourth, priming should no longer be effective, as an item that is lost obviously cannot be primed. Fifth, if the knowledge is lost then performance should be independent of the presentation rate, whereas disturbances of access should be sensitive to the rate of presentation of the material. 34
  35. 35. The structure of semantic memory: Evidence from studies of dementia Dementia is a general label for the widespread decay of cognitive functioning, generally found in old age. The ultimate causes of dementia are unknown, although it is likely that both genetic and environmental factors play some role, and it is clear that there are several subtypes, the most common of which is Alzheimer’s disease (AD). In dementia, memory and semantic information are particularly prone to disruption. 35
  36. 36. Semantic memory disturbances in dementia There is a huge body of work indicating problems with semantic processing in dementia. People with dementia are often impaired on the category fluency task, where they have to list as many members as possible of a particular category (e.g., Martin & Fedio, 1983). They have difficulty listing attributes that are shared by all members of a category (Martin & Fedio, 1983; Warrington, 1975). They have difficulty in differentiating between items from the same semantic category (Martin & Fedio, 1983). They tend to classify items as being similar to different items more than controls do (Chan et al., 1993a, 1993b). They are also poor at judging the semantic coherence of simple statements: For example, they are more likely to judge “The door is asleep” to be a sensible statement than controls (Grossman, Mickanin, Robinson, & d’Esposito, 1996). 36
  37. 37. Difficulties with picture naming People with dementia often have difficulty in naming things. There is evidence that the semantic deficit is involved in picture naming. Most of the naming errors in dementia involve the production of semantic relatives of the target (e.g., Hodges, Salmon, & Butters, 1991). The extent of the naming impairment is correlated with the extent of the more general semantic difficulties (Diesfeldt, 1989). Naming performance in dementia is sometimes affected by the semantic variable of imageability. With other types of neuropsychological damage, patients usually find high- imageable items easier than low-imageable items. 37
  38. 38. Connectionist Approaches to Semantics Connectionism has made an impact on semantic memory, just as it did in earlier years on lower level processes such as word recognition. This approach gives rise to the idea that semantic memory depends on semantic microfeatures. Note that this approach is not necessarily a competitor to other theories such as prototypes; one instance of a category might cause one pattern of activation across the semantic units, another instance will cause another similar pattern, and so on. 38
  39. 39. Semantic microfeatures A microfeature is an individual, active unit; the prefix “micro” emphasizes that these units are involved in low-level processes rather than explicit symbolic processing (Hinton, 1989), but there really isn’t much difference between a feature and a microfeature. Connectionist models suppose that human semantic memory is based on microfeatures. A semantic microfeature is really just a semantic feature, but the prefix “micro” is added in computational modeling to emphasize their low-level nature. 39
  40. 40. Explaining language loss in people with Alzheimer’s disease: The semantic microfeature loss hypothesis What happens if a disease such as dementia results in the loss of semantic microfeatures? The effect will be to distort semantic space so that some semantic attractors might be lost altogether, while others might become inaccessible on some tasks because of the erosion of the boundaries of the attractor basins. Damage to a subset of microfeatures will lead to a probabilistic decline in performance. Depending on the importance of the microfeature lost to a particular item in a particular patient, the pattern of performance observed will vary from patient to patient and from task to task. Different tasks will give different results because they will provide differing amounts of residual activation to the damaged system. 40
  41. 41. 41
  42. 42. 42 Thanks! Any questions? You can find me at atta.saeed@gmail.com
  43. 43. 43 Ata Mohammed Saeed M.A(ELT) student University of Kurdistan 21th Nov 2021