Why is dialect so important

In addition, different locales have their own languages and, often, their own dialects. Language and dialects preserve the unique cultural elements of a given place. As people travel more frequently, they exchange goods and ideas.

Thus, the blending of cultures has become easier and more commonplace. In the age of globalization, one may argue that language acts as a barrier to communication. Individual dialects may divide people even further. However, dialects express the unique qualities of a particular region. Dialects are important for international business and the overall well-being of our world.

Read on to learn how. Dialect is a very powerful and common way of characterization , which elaborates the geographic and social background of any character. One of the best dialect examples in literature, in which it is used as a literary device, occurs in this piece by Mark Twain. Here, Twain uses exaggerated dialect to distinguish between the characters. Characters that are less educated and less sophisticated are usually shown to be speaking with a much stronger dialect.

At certain points you might even need translations. Such as:. Mean cross-entropy error in the reading task was computed for all word pairs. Contrastive words had much higher error than Non-contrastive words in the Mismatch model, with little difference between the two word types in the MAE Match model with similar results for the AAE Match condition. These results are consistent with the behavioral data presented above.

The Contrastive and Non-contrastive stimulus words in the experiment were equated on many other factors known to affect reading difficulty and were chosen to be equally difficult for speakers of MAE. Thus, the factor that makes the Contrastive words more difficult, for both the model and for higher AAE-use children in the behavioral experiment, is having different pronunciations across the dialects. Beyond its relevance in showing that it is pronunciation mismatch, not AAE itself that is the main source of difficulty for the model, the AAE Match condition is also relevant to an educational issue, whether teachers should correct children's AAE pronunciations in the classroom Labov, ; Goodman and Buck, The fact that performance in the Mismatch condition was much poorer than in the AAE Match condition as well as the MAE Match condition is consistent with the conjecture that learning is easier if AAE speaking children are permitted to use AAE pronunciations, rather than having MAE pronunciations provided as corrections when they are reading aloud.

Repeated correction of a child's use of AAE phonology might also be contraindicated by its potential negative impact on children's attitudes about their language and on motivation to learn Seymour and Seymour, ; Ladson-Billings, Our models do not address these socio-cultural issues, and indeed the AAE Match condition instantiated in the model is an idealization in which only AAE pronunciations are utilized—in effect simulating a situation in which the MAE dialect does not exist anywhere in the child's experience.

Thus, even if AAE pronunciations are not corrected in the classroom, children may gain such feedback from other experiences, such as hearing MAE pronunciations and recognizing mismatches with their own speech.

Social and cultural expectations about the use of mainstream vs. In summary, Simulation 1 created a clear test of some effects of dialect on learning to read, setting aside many factors that are confounded with dialect use in naturalistic settings. The results suggested that AAE phonology by itself, although it makes the spelling-sound correspondences more inconsistent than the already inconsistent correspondences in MAE, increases the difficulty of learning these mappings by only a small amount.

The existence of two pronunciations for Contrastive words, however, yielded a substantial burden for both the model in the Mismatch condition and the bi-dialectal children in the experiment. Two main mechanisms appear to underlie these effects. First, the number of unique phonological word forms to learn is larger in the Mismatch condition all of the alternative pronunciations of the Contrastive words.

In short, the Mismatch Model performed a more complex learning task than the Match models. Simulation 2 examined two additional factors. First, many children are exposed to both dialects prior to school, in varying proportions. Children who are already familiar with the alternative pronunciations of words may have less difficulty learning to use MAE in learning to read and other classroom activities.

We created a Bi-dialectal condition, in which the model was trained to produce both AAE and MAE pronunciations during the speech phase, to examine this possibility.

Second, children learn words in contexts that convey information about the existence of dialects, the differences between them, and the conditions under which they are used. Many speakers successfully learn to represent both dialects and switch between them Terry et al. The Simulation 1 results show that learning the alternative pronunciations and their relations to spelling is a more complex task, requiring additional learning trials.

In Simulation 2, we examined whether the impact of the increased complexity of the task is mitigated by introducing the alternative pronunciations earlier before the reading phase and providing contextual cues for using AAE or MAE. The Bi-dialectal models in Simulation 2 used the same architecture as in the first simulation and again had a speech training phase followed by a reading phase with continued speech trials interleaved with reading.

The training of the Bi-dialectal models was changed so that the models produced both AAE and MAE pronunciations in the speech phase, followed by learning to map spellings onto MAE pronunciations in the reading phase. MAE pronunciations were used in the reading phase both because schools emphasize using MAE, and to permit comparisons to the results of the Mismatch condition in the previous simulation, which showed that learning to produce MAE pronunciations on reading trials after AAE exposure in the speech phase was difficult.

The Bi-dialectal conditions thus addressed whether production of MAE pronunciations prior to the onset of reading would be helpful in making the transition to MAE usage in reading. For Non-contrastive words in the training set, the model was presented with input and had to maintain the pronunciation, as in the previous simulations. Each pronunciation target AAE or MAE was assigned half the overall frequency of the word, meaning that for Contrastive words, the model had to produce AAE pronunciations approximately half of the time and MAE pronunciations the other half.

This procedure created variable pronunciations for the Contrastive words and gave the model experience producing the MAE pronunciations before the onset of reading. Three Bi-dialectal conditions were developed, differing only in the use of the context units shown in Figure 2 , which provided contextual cues to help the model distinguish AAE and MAE pronunciations.

These two units indicated whether the model should produce AAE or MAE and served as proxies for a variety of cues that allow speakers to learn alternative dialects and switch between them. The context units were not used in the speech phase for any of the models, and thus all models had identical pre-reading experience in this simulation. In the Early Context condition, the context units were used at the onset of the reading phase. For all reading trials, the MAE context unit was on, indicating that the model should produce an MAE pronunciation for the print input.

The context units had the same effect in the Late Context condition, except that they were not used until halfway through the reading phase. Finally, in the No Context condition, the context units were never used for any reading trials or speech trials in the reading phase. The number of epochs in the speech training phase was matched to the number of epochs used in Simulation 1. The Bi-dialectal models were then trained to produce MAE pronunciations in the reading phase for epochs, as in Simulation 1.

Reading performance was scored as in the previous simulation. Figure 4 shows percent correct performance in generating MAE pronunciations on reading trials, with the MAE Match condition from Simulation 1 included for comparison.

The figure shows that on the reading task, learning was slower in all of the Bi-dialectal conditions than in the MAE Match condition. The Bi-dialectal conditions were harder for several reasons. In the speech phase, the model had a larger number of distinct phonological patterns to learn than in Simulation 1, but with the same number of training trials, which resulted in poorer speech performance.

The reading trials were also more difficult: the model had to both consolidate the MAE pronunciation and learn to generate it from the word's spelling, while training on both MAE and AAE pronunciations continued during the interleaved speech trials.

The net result was that learning also occurred more slowly on the reading trials. Figure 4. Model performance on the reading task in the Bidalectal conditions compared to the MAE Match condition from Simulation 1. These effects were greatly ameliorated by providing context cues. In the Early and Late Context conditions, the contextual cue was provided for interleaved speech trials beginning at epoch 0 in Figure 4 for the Early Context Condition and at epoch for the Late Context condition.

Although the prior speech phase was identical for these models and the reading trials were identical with the context units always signaling an MAE pronunciation , context cues during the speech trials varied within the reading phase, indicating either AAE or MAE pronunciations for Contrastive words.

Figure 4 shows that including the context cue was helpful, with both Context conditions showing better reading performance than the No Context condition. The Early Context condition yielded reading performance very close to the MAE Match condition at the completion of the epochs of reading training; the Late Context cues were also effective, although additional training trials would be needed for performance to fully catch up.

These results suggest that cues to the alternative pronunciations in speech has an impact on learning to decode. Merely introducing both pronunciations early in training as in the speech phase in these models did not improve reading performance in the simulations. However, the two Context conditions show that additional information that helps the model partition the two dialects greatly improves reading performance, particularly in the Early Context condition.

Again it should be noted that the models are simplified in many respects. All of the information relevant to learning about dialects, their properties, and the conditions under which they are used was captured by a single context cue. Moreover, the cue was wholly reliable and unambiguous, whereas the cues that exist in naturalistic contexts are not. The contextual cues were also introduced relatively late, at the onset of reading, whereas many children will have begun acquiring conscious or unconscious knowledge about dialectal variation earlier.

Nonetheless, the main results are clear: Considered just in terms of the complexity of what has to be learned, the existence of alternative pronunciations complicates both the speech and reading tasks, and the provision of dialect-distinguishing cues is helpful.

We conducted one experiment with young readers and two computational simulations investigating the role of dialect on learning to read English. Both the behavioral and modeling evidence indicate that knowledge of alternative dialects affects acquisition and use of spelling-sound knowledge, an important component of reading. The experiment and simulations show that the locus of these effects is the Contrastive words, which have different presentations in the two dialects, whereas Non-contrastive words are largely unaffected by knowledge of two dialects.

Previous research has shown that spellings that are associated with different pronunciations are harder to pronounce. In these cases, two semantically unrelated words with different pronunciations happen to be spelled the same.

Contrastive words in AAE have a single meaning, but as in the other cases, a single spelling is associated with two pronunciations, increasing the difficulty of reading aloud. Thus, the effects of dialect can be understood as the natural consequence of the added ambiguity of the mapping between spelling and pronunciation for a subset of words.

The computational simulations produced similar effects, in models that excluded factors such as SES, school or home environment, and intelligence. The computational results suggest that the existence of two pronunciations for a word creates additional complexity both with respect to spoken language learning different pronunciations of a contrastive word in the Bi-dialectal models in Simulation 2 and in learning the relations between spelling and phonology.

Other factors that may affect performance need to be considered in future behavioral and computational work. Among the most important are a other phonological differences between dialects; b individual differences in dialect density, the extent to which an individual uses AAE features; c impact of vocabulary size and quality; and d the role of semantics in linking different pronunciations.

It would also be important to address contextual cues in a richer way, taking into account their real-world variability and developmental changes in children's capacities to utilize such information.

The models demonstrate that the knowledge of variable pronunciations can affect learning, but they do not predict outcomes for individuals.

The fact that the model, which excludes many factors that affect children's school performance, nonetheless reproduces the difference between Contrastive and Non-contrastive words permits some specific, though tentative inferences about the impact of dialect on early reading.

The effect was not due to properties of AAE. The AAE Match model in Simulation 1 performed nearly as well as the MAE Match model, indicating that the additional irregularity from consonant deletion and other aspects of AAE phonology had a minimal effect on reading performance. The effect was not due to characteristics of children such as IQ, or to environmental factors such as differences in instruction or opportunity, none of which were incorporated in the model.

Rather, the effects emerge from conflicts between the dialects which are relevant because of social and cultural conditions governing their use, specifically the fact that MAE is the dialect of instruction Children who mainly speak AAE and then are expected to use MAE in reading and other school activities have more to learn than children who only use the mainstream dialect.

Results from the Mismatch condition suggest that the additional load is substantial. Our results relate to several issues that have contributed to controversies about dialect differences and the achievement gap. Previous research of the impact of dialect differences on reading yielded mixed results. There are multiple differences between MAE and AAE, only some of which may be relevant to reading and school performance.

We focused on a specific characteristic linked to a specific component of learning to read, decoding. Our hypotheses about the possible relationship between dialect and decoding were motivated by extensive research on properties of spelling-sound mappings in English that affect decoding in children and adults. This research only addressed a single dialect difference. Other theory-driven hypotheses relating dialect properties to reading and school achievement should be addressed in future research.

The present results are also relevant to questions about the impact of dialect on reading compared to differences in knowledge of spoken language that are not dialect related. Reading acquisition is strongly related to knowledge of spoken language, including vocabulary and phonological awareness National Reading Panel, AAE speakers' poor reading achievement could reflect weaknesses in these areas, as in MAE speakers, rather than dialect per se Terry and Scarborough, Dialect use and spoken language skills are not mutually exclusive Terry and Scarborough, ; Seidenberg, ; both are likely to contribute to reading outcomes Edwards et al.

The decoding effects that we have observed clearly derive from dialect differences, however: First, in both the children and in the simulations, the effects are limited to Contrastive words for which the ambiguity of spelling-sound mapping increases difficulty. Second, the effects of dialect use in the children arise even after vocabulary size is taken into account in the analyses.

These results suggest that the effects of knowing multiple dialects are substantial, and it will be important to determine the degree to which individual difference and environmental factors not considered here exacerbate or mitigate these effects Washington et al.

Finally, our results can be related to other recent studies attempting to identify factors contributing to the achievement gap. Econometric analyses suggest that the reading gap in kindergarten children can be explained by factors related to SES. However, they do not explain why the gap grows larger over the first few years of schooling Fryer and Levitt, Importantly, the large datasets on which such analyses are based do not include measures of characteristics of the child's speech and the spoken language environment, including the use of a non-mainstream dialect.

The gap's increase may be due in part to the mounting impact of linguistic factors as curricular demands increase. In summary, our research pinpoints how a difference between dialects can affect acquiring an important reading skill. Children are nonetheless evaluated against the same achievement milestones.

Although we deliberately set aside SES, oral language skill, and other factors in order to focus on the effects of dialect, it is likely that the dialect-related differences observed here are exacerbated in children with weak oral language skills and other challenges. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

However, the benefits of training are difficult to maintain because speakers use Japanese outside the laboratory context, reinforcing the native phonological system.

The interleaving of experiences with the two phonological systems works against acquiring the new phonological contrast. Similarly, children may benefit from the non-correction of AAE pronunciations in the classroom, but the impact may be vitiated by continued exposure to and use of MAE pronunciations in other contexts.

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Dunn, L. Edwards, J. To use vivid language is to use imagery in your language, to describe something as vividly as possible. Inclusive language means using language that does not exclude any person. It also means avoiding any language that is racist, sexist, misogynist, hateful, presumptuous, prejudiced, etc. With technology comes trends or different ways of speaking, like how many teenagers or young people use slang when they speak. When societies become more open-minded and progressive, we start accepting that there are many other ways of speaking language.

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