T HEORETICAL B ACKGROUND
1.5 Psycholinguistics and Bilingualism
1.5.1 Models of Bilingual Language Representation and Processing
When it comes to aims of research on bilingualism, development of models on how the language of the bilingual individual is acquired, represented and processed has been of primary interest irrespective of the methodology of reasearch—be it descriptive, theoretical or experimental. Multifarious models have evolved over time depicting the representation of words in dual languages and the inherent interconnectivity between them. In models pertaining to lexical representation and processing, it has been observed that a clear demarcation is made between form representations and their inherent meaning. Further, in discussion of language processing models in bilingualism, a striking area of differentiation that emerges is that between language comprehension and its production. Most available models are specific to either of them and cannot be applied interchangeably. The following section gives a brief overview of some of the major bilingual word recognition and production models developed within the theoretical framework of cognitive psychology.
1.5.1.1 Models of word recognition
The most common view of bilingual lexical memory is that it is ‘hierarchical’ in the sense that it consists of at least two layers of memory representation (or ‘nodes’)—a
general level (i.e., the conceptual level) and the language-specific mental lexicons.
In the following sections we discuss briefly three hierarchical models.
The Word Association and Concept Mediation Models.
In 1984, Potter et al. proposed two hierarchical models, namely, the Word Association Model and the Concept Mediation Model, with respect to retrieval of word knowledge in the lexicon of the bilingual. These models have been around under different names much longer (see Weinreich, 1953). According to the Word Association Model, lexicons are connected directly by means of word connections. According to Concept Mediation Model, the lexicons are related only via their connections with the conceptual information, which is common for both languages (see Figure 1.1).Figure 1.1 (a) The Word Association Model and (b) the Concept Mediation Model (adapted from Potter et al., 1984).
Initially, the various psycholinguistic models did not account for the possibility that bilingual memory may be a function of second language proficiency and translation direction. To account for this, Kroll & Sholl (1992) and (Kroll & Stewart (1994) introduced a third version of the hierarchical model by incorporating both the word association and the concept mediation models into the same model (see next section).
The Revised Hierarchical Model (RHM).
The Revised Hierarchical Model by Kroll & Stewart (1994) is one of the most well-known models of bilingual lexical(a) Word Association Model (b) Concept Mediation Model
L1 L2
Concepts
L1 L2
Concepts
representation. The model is similar to the earlier hierarchical models in terms of basic structure—it proposes two independent lexicons, one for each language, and an integrated conceptual system. However, the model also captures the inter- language connections between lexical and conceptual representations as learners become more proficient in their second language. Two core assumptions of the model are (1) links to the conceptual system are stronger in case of L1 lexical items, whereas in case of L2 lexical items, lexical links between word forms are stronger (see Figure 1.2), and (2) high proficient bilinguals can map an L2 word to the conceptual system directly, whereas low proficient bilinguals initially map an L2 word onto its L1 translation, and then access the conceptual system via the lexical and conceptual representation of the L1.
Figure 1.2 The Revised Hierarchical Model (adapted from Kroll & Stewart, 1994).
In the following section, we will discuss two models which differ from the hierarchical models in that these models assume bilingual memory structures with distributed meaning representations. In these models, the meaning of a word is spread out over a number of more elementary meaning units that each stores one elementary part of a word’s meaning (e.g., De Groot, 1992a, 1992b; Taylor, 1976) and the word form representations are also distributed over a number of more elementary features, this time form features (e.g., Kroll & De Groot, 1997; Van Hell
& De Groot, 1998a).
The Distributed Conceptual Feature Model (DCF).
The Distributed Conceptual Feature Model was proposed by De Groot and colleagues (De Groot,L1 L2
Concepts Lexical Links
Conceptual Links
1992a, 1992b, 1993; De Groot et al., 1994; Van Hell &De Groot, 1998a, 1998b). As per the assumptions of this model, a shared conceptual system exists for both L1 and L2, but the conceptual representation is in the form of distributed features.
Moreover, the degree of overlap between L1 and L2 representations is primarily dependent on word type (see Figure 1.3). For example, translation is easier when the words from two different languages share many semantic features, as opposed to when they share limited semantic features.
Figure 1.3 The Distributed Conceptual Feature Model of bilingual memory representations for different word types (adapted from De Groot, 1992a).
The interconnectedness of words across languages is well captured in this model.
However, it is limited in the sense that only findings at the word level are explained by it, whereas other general findings, such as the role of translation direction or the role of proficiency cannot be explained by this model. The next section discusses a model by Finkbeiner et al. (2004) who have proposed interesting modifications to De Groot’s Distributed Conceptual Feature Model.
The Sense Model.
To account for the bilingual translation priming asymmetry observed in previous studies, Finkbeiner et al. (2004) proposed the Sense Model which gives an alternative to the DCF model. Instead of focusing on the varying number of meaning and form elements different translation pairs may share, the authors focused on clusters of meaning elements that each constitute a word sense (De Groot, 2011). According to this model, each member of a pair of translationsL1 L2
Casa House
(a) Concrete
L1 L2 L1 L2 Lexical
Level
Conceptual Level Amor Love
(b) Abstract
Hospital Hospital
(c) Cognates
has language-specific senses in addition to the one or more senses that it shares with the other member of the translation pair and the ratio of the primed senses to the unprimed senses determine priming. Thus, as per the predictions of the model, not only the overlap in the semantic senses activated by the prime and target determines translation priming, but it also depends on the ratio of the primed to unprimed senses associated with the target. Moreover, the model explains the asymmetry in translation priming by proposing that a bilingual speaker would normally know more senses in their L1 words as they are more proficient in their L1 as compared to L2 words. This results in significant priming in L1−L2 than from L2−L1 (see Figure 1.4).
Figure 1.4 A schematic representation of the Sense Model (adapted from Finkbeiner et al., 2004).
In the present decade interesting trends have emerged for the description of bilingual lexical organization by the application of the connectionist framework. A main feature of connectionist models is the way they represent information. Connectionist models are divided into local representation models and distributed representation models. In the next section few local connectionist models for word recognition are briefly reviewed.