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Introduction of Mental Lexicon
Mental lexicon denotes a collection of words in the mind of any individual. According to linguists, it is a part of one’s grammar that encloses all the information linked to the words and morphemes including morphological, phonological, semantic, and syntactic (Dell et al., 1997). Psycholinguists have observed that words are stocked up with its phonological as well as orthographic shapes. Language impaired individuals have been a good source of information about lexicon through analyzing their speech errors including malapropisms, paraphasias, and lexical decision tasks (Sripada, 2008). Lexical decision tasks include the deciding act of a subject regarding the word selection and time taken in the judgment of the word. How words are arranged in the mind, memorized, retained and retrieved by the region of the mental lexicon, have been significant questions. Every act of linguistic communication is facilitated by an organized lexicon (Sripada, 2008; Dell et al., 1997, Elman, 2004).
Theories on Mental Lexicon
Several theories are proposed to describe the word organization in the lexicon. One theory cited that lemmas act as a container of words, its meanings; if the word is a verb then its function and execution pattern in a sentence (Dell, 1997). Lemmas are an abstract conceptual form of a word that encodes the message grammatically and at the same time they stimulate the lexemes or the spoken word outline. Whenever a word is stimulated all the relevant data of that word is activated, such as its homophones, syntax, meaning, orthography, and emotional content. This phenomenon explains the complexity and networking of the mental lexicon (Bastiaanse & Van Zonneveld, 2004).
Semantic network theory proposes that stands on the spreading phenomenon on the stimulation of any semantic node which may be three distinct ways, priming, neighborhood and frequency effects. Priming denotes the activation of linked words on stimulating a single word. Neighborhood effect belongs to the activation of phonologically closed words on activation of a single word, and those may further stimulate other neighborhood words. Frequency effect states that frequently spoken words are quickly recognized by the lexicon. High-frequency words are responded quickly in comparison to low-frequency words (Forster & Chambers, 1973). Another common theory is spectrum theory which states that every phonological shape of the word is connected to a complex semantic representation while polysemes and homonyms show their unique semantic representations (Brown, 2008). Dual coding theory (DCT) involves an internal nonverbal and a verbal system. Nonverbal structure signifies the perceptual characters and affordance of nonverbal events and objects while verbal system interferes with linguistic stimuli and responses (Paivio, 2010).
Word characters at distributional levels
Various linguists have observed the frequency effect of the words. Zhou and Marslen-Wilson (2000) evaluated the frequency difference between monomorphemes and compounds through employing differential frequency effects (Zhou & Marslen-wilson, 2000).
The influence of lexical variables includes frequency and imageability that have a significant role in the architecture of word production. Frequency refers to the occurrence rate of words in a speech corpus while imageability is the ease of creating a mental image for the words (Balota and Chumbley, 1985). Both of these variables are important indices to mental lexical access. Nozari et al. (2010) discussed the findings of a comparative analysis between normal and aphasic subjects. The outcomes of the analysis reveal that the normal subjects demonstrate a frequency influence in the repetition of a word list while aphasic subjects demonstrate more accuracy while repeating the single words which are high in frequency as well as imageability (Nazare et al., 2010). In the lexical decision task, it was found that subjects faced more difficulty in responding to low-frequency words in comparison to high-frequency words because low-frequency words were homologous to the non-words on the basis of a familiarity dimension. Thus, it is concluded that lexical decision task shows slow responses to low-frequency words as compared to high-frequency words (Balota and Chumbley, 1985; Libben et al., 2003; Baayen et al., 2011).
A regression analysis by Nazare et al. (2010) revealed that the frequency effect observed in the picture naming exists in auditory words repetition. Moreover, it was found that the lexical root model defining the repetition demonstrate a comparable frequency influence to the naming model. These findings were very interesting and provided certain new insights in frequency effects. Proposed models of normal word production showed well-established concepts of message articulation. It is evident that the frequency effect of well-known or familiar words emerges at the lexical access level earlier. High-frequency words are recognized with a faster pace. Balota and Chumbley (1985), presented the evidence that the word frequency can control the speed of articulation while pronunciating words especially in normal subjects (Bose et al., 2007; Balota and Chumbley, 1985).
On the basis of structural word level, it is necessary to understand the frequency distributional character of monomorphemes and compound words regarding the linguistic stimulus. Bose et al., used a verbal repetition task to analyze the levels of a frequency distribution in whole words (word frequency) and words composed of more than one components (bigram frequency). Frequently used words are represented as whole units and accessed more easily that show high frequency produced at faster rates with the possibility of fewer errors. For the fewer frequency words, the articulation processing is believed to be executed in segments. Thus, the words with low frequency take longer reaction time and have a possibility of longer word durations. Moreover, these are prone to errors. It is seen that high-frequency non-words with the second syllable demonstrate longer durations in comparison of low-frequency non-words (Bose et al., 2007).
In clinical, behavioural tasks, it is noticed that aphasic subjects named higher frequency words more accurately showing shorter latency for high-frequency words (Bose et al., 2007).
Word characters at Structural levels
On the structural basis, the words in linguistic are divided into two main types, monomorphemes, and polymorphemes (Dell, 1997). Monomorpheme is a word consists of just one morpheme. On the contrary, polymorphemes consist of more than one morphenes in a compounding process; these are termed as compound words. Such as, “Tea” is a single morpheme that can not be broken into further units while “teapot” is a compound word made up of two separate morphemes. Compound words are more complicated than monomorphemes thus, harder to lexical access (Delazer & Semenza, 1998; Elman, 2004).
According to Zhou & Marslen-wilson, (2000), the phonological and semantic transparency of a compound or polymorphemic word impacts its representation to the lexicon. It also impacts the decomposition of the auditory and visual input into monomorphemes at the lexican site. Morphology depicts the study of word structure; syntax is for sentence structure analysis while semantics is the meaning analysis of a word. To study the word processing in the mental lexicon for monomorphenes and polymorphenes it is necessary to understand the different morphological processes including derivational, inflectional and compounding measures. Derivational and inflectional morphology varies in the case of English compounding that involves a mixing of stem morpheme with a bound morpheme, where word owns an affix and without it, word has not any meaning to the lexicon. Inflectional, as well as derivational morphologies represent the word in semantic and combinatorial fashion, respectively (Zhou & Marslen-wilson, 2000).
A compound word is a set of two free stems and on the inflectional and derivational level, its meaning can never be straightforwardly predicted on a compositional basis (Zhou & Marslen-wilson, 2000). The semantic unpredictability of compound words confronts to the morpheme-based model of lexical representation that highlights its representation in the form of listed or linked morphemes. Moreover, based on multiple languages analysis, it is concluded that orthographic form of compound words is presented as a concatenation of the orthographic forms of their constituents together. Thus, it can be said that the phonological and orthographic relations between compound words and their morpheme units are evident (Libben et al., 2003; Zhou & Marslen-wilson, 2000).
It is concluded that polymorphemic words are recognized in two ways, in a whole-word representation accessible in the lexicon via a holistic pattern and through accessing the meanings of its components via a decomposition route (Hyona, 2015). In a repetition priming experiment, the whole words and constituent morphemes were evaluated based on its priming for pseudo-compounds, semantically transparent and opaque compound words. The former word type presents a letter string related to a real morpheme (Libben et al., 2003). While latter two words, whose meanings are either synchronically connected or there is no relation between them and their constituents’ meaning. The results showed similar priming effects for all these three types which proved that the morphology of a word along with its semantic lucidity impact the processing of compound words to the mental lexicon (Zhou & Marslen-wilson, 2000).
Processing of the compound and monomorphemes to the mental lexicon
The latest approach to word production is based on a two-step lexical access. The first step is an appropriate lexical component or lemma is selected. At this stage, the syntactic and semantic information about the word is stored (Dell, 1997). On achieving the semantic conditions, lemmas are activated and stimulate the syntactic procedures. The second step of the procedure involves the retrieval of the phonological order of the words (using lexemes). For the compound word processing, it is believed that a single lemma provides a single abstract representation of a polymorphemic word (Bastiaanse & Van Zonneveld, 2004). Thus, the Compound words must be processed like monomorphemic words. The second approach suggests that the compound words can be produced by joining of two lemmas. The two components of the compound words at the lemma level would be presented as two different morphophonological forms. It also requires a single lexical entry that specifies the two lemmas (Bastiaanse & Van Zonneveld, 2004; Zhou & Marslen-wilson, 2000).
On the basis of a case study Belazer and Semenza (1998), supported the hypothesis of two lemmas that are involved in the retrieval of compound words. Further studies reveal that polymorphemic words are recognized using both patterns, a whole-word pattern, and decomposed-word pattern. In the whole word approach, the compound word is represented to the lexical access as a whole-word which is described through holistic route. Another approach regarding the compound word to lexical access is the recognition of word through identifying the meanings of its components using the decomposition route (Hyona, 2015). The length of words also determines the route of access while processing the compound words. The decomposition route is found more prevalent in long polymorphemic words (Hyona, 2015).
Distributional frequency based models for morphological processing suggests that these both processing routes can be identified by analysing the frequency effects, either the surface or base frequency.
The semantic, as well as the phonological steps, are included in the naming process, but the semantic step is not needed in repetition. Repetition could involve the retrieval of word’s output phonemes from the lexicon and phonology of the output from input phonology via lexical-route and nonlexical-route model, respectively. It also can employ the both routes or the summation dual-route model. The extent of the frequency effect has been analogous to repetition and naming processes and has been large for the lexical access and summation
dual-route models. The dual-route model showed consistency inferring that the nonlexical input is combined with a fully-utilized lexical route (Nozari et al., 2010).
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