32.2406, Review: Cognitive Science; Linguistic Theories; Psycholinguistics; Semantics: Bolognesi (2020)

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Subject: 32.2406, Review: Cognitive Science; Linguistic Theories; Psycholinguistics; Semantics: Bolognesi (2020)

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Date: Fri, 16 Jul 2021 17:31:33
From: Heli Tissari [heli.tissari at helsinki.fi]
Subject: Where Words Get their Meaning

 
Discuss this message:
http://linguistlist.org/pubs/reviews/get-review.cfm?subid=36709117


Book announced at http://linguistlist.org/issues/32/32-34.html

AUTHOR: Marianna  Bolognesi
TITLE: Where Words Get their Meaning
SUBTITLE: Cognitive processing and distributional modelling of word meaning in first and second language
SERIES TITLE: Converging Evidence in Language and Communication Research 23
PUBLISHER: John Benjamins
YEAR: 2020

REVIEWER: Heli Tissari, University of Helsinki

SUMMARY

Marianna Bolognesi’s book “Where Words Get their Meaning” deals with profound
issues. The subtitle “Cognitive processing and distributional modelling of
word meaning in first and second language” gives us important information
about her approach, which is informed by distributional modelling and studies
on first and second language learning. The book is divided into three parts,
“Word meaning construction and representation in the human mind” (Chapters Two
to Four), “Word meaning construction and representation in the artificial
mind” (Chapters Five to Seven), and “Converging evidence in language and
communication research” (Chapters Eight to Ten). 

The first chapter of the book is called “Word power”. In it, Bolognesi briefly
discusses the effects of word choices, but it is, above all, an overview of
what is to come. Bolognesi summarizes her topics in the form of three
questions (p. 8): “How do the word-to-world and word-to-word associations
contribute to the construction of word meaning in our mental lexicon? How do
children and adult language learners learn new word meanings? And what can the
latest endeavors in machine learning and AI contribute to our understanding of
the structure and functioning of the human mental lexicon?” 

In the first part of the book, Bolognesi focuses on the question of how people
learn new words. The second chapter is titled “Word meaning mental
representation”, and it takes a developmental perspective. Bolognesi begins
with pointing out four biases in the learning of concrete nouns. The whole
object bias suggests that a new encountered noun refers to an entire object.
The taxonomic bias suggests that when a new word is spoken in the same context
with an old one, the two words belong to the same taxonomic category (e.g.
animal). The basic level bias suggests that a new word refers to an everyday,
basic level item; and the mutual exclusivity bias suggests that each single
word denotes a single object of its own. On this premise, which she points out
is insufficient to explain word meaning acquisition, Bolognesi introduces
cross-situational learning whose idea is that children are able to deduce
meanings of words on the basis of encountering them in  different new
situations and making comparisons between these situations. This is easiest in
transparent situations where both the word and the object it refers to are
present. Bolognesi suggests that children may associate concrete things even
with abstract nouns but continues to explain that abstract nouns can above all
be learned via language. In other words, in some situations language learners
infer the meaning of a word from the physical context, while in others they
infer it from the linguistic context. 

In Chapter Three, “Word meaning extension: Deriving new meanings from old
ones”, Bolognesi discusses some common mechanisms through which words acquire
new meanings. These comprise polysemy, metonymy and metaphor. In this chapter,
she defines the term ‘mental lexicon’ as follows (p. 34):  “--- I refer to
mental lexicon as a virtual (rather than physical) architecture that collects
all the knowledge and information (derived from language and from experience)
about a word and allows the different streams of information to interact,
combine and inhibit one another, depending on the context and the task
conditions in which the speaker is involved.” 

Bolognesi does not only discuss the phenomenon of polysemy but also Word Sense
Disambiguation (WDS) and computer programs aimed at detecting different senses
of words. She seems at the same time skeptical and hopeful of unsupervised
methods in this respect. As regards the discussion of metonymy, she introduces
two psycholinguistic models. According to one of them, people primarily access
the literal senses of words, whereas figurative senses are accessed
indirectly. According to the other model, neither the literal nor figurative
senses of words are systematically prioritized, but “contextual and lexical
information determine the intended meaning” (p. 42). She continues with the
topic of literal versus figurative senses in the subchapter on metaphor where
she also suggests that metaphors violate Grice’s maxim of quality by not being
true. Moreover, she continues to ponder computer programs that would
automatically identify metaphorically used words and analyze them. She tells
us that the “problem of automatic metaphor identification is very challenging”
(p. 49) but continues to evaluate some existing work. She also asks to what
extent computer programs correspond to what occurs in the human mind. 

In Chapter Four, “The bilingual mind and the bilingual mental lexicon”,
bilingualism enters the scene. Bolognesi begins it by introducing Kroll and
Stewart’s (1994) Revised Hierarchical Model for bilingual lexicon, according
to which second/foreign language learners first translate each word they
encounter into their first language and are then able to access its conceptual
representation. As their fluency in the new language grows, this strategy
gradually falls out of use. According to Bolognesi, the merit of this model
was that it distinguished between the mental representations of words and
concepts, but she continues to report newer, brain imaging studies. These show
not only overlap and divergences between L1 and L2 but also that bilingual
brains seem to function differently from monolingual brains. Again in this
chapter as well as in the previous ones, Bolognesi calls for a dynamic,
bottom-up approach to language learning. She compares word associations in
native speakers and language learners and proceeds to talk about incidental
vocabulary learning. Incidental vocabulary learning occurs when a person
encounters the same word several times in similar enough contexts to be able
to deduce its meaning. Bolognesi points out that this is a good way to learn a
new language provided that the texts the learner reads are on just the right
level of difficulty. She then proceeds to also pointing out that incidental
learning is a form of statistical learning. The main message of the chapter
comes towards its end, where Bolognesi emphasizes that pattern detection is a
hallmark of human cognition. She discusses pattern detection in detail,
dividing it into world-to-world, word-to-world and word-to-word associations.
She further divides these associations into syntagmatic and paradigmatic,
distinguishing between the company an item keeps and items that occur in
similar contexts. This takes her directly to the second part of the book where
she discusses the artificial mind.

Chapter Five is titled “Distributional models and word embeddings”. It
contains a wireframe model of how we can calculate conceptual distances
between various words based on the contexts in which they occur. This is
illustrated with the help of images and tables. The chapter also contains
mathematical equations used to produce distributional models. The focus is on
Latent Semantic Analysis (LSA). Bolognesi explains how vectors can be used to
describe the positions of different words in conceptual space. She briefly
covers different macro types of distributional models when she discusses
structured and unstructured models, explicit and implicit vectors, and
compares frequency-based models with word embeddings. 

Such basic information having been provided for, Bolognesi directly continues
to “Evaluating distributional models” in Chapter Six. The measure by which she
evaluates the models is how well they correspond to human cognitive
functioning. After talking about synonym tests and conceptual priming, she
critically discusses Pavlov’s dogs, pointing out that it is not only positive
associations that count, but also the things that do not happen (Rescorla
1988). In other words, learners evaluate both positive and negative evidence,
presence and absence. This helps us to understand that foreign language
learners rely more on linguistic cues than embodied situational evidence,
since the former is more available to them. In this chapter, Bolognesi
discusses two of her own studies in detail, illustrating differences between
language learners and native speakers (2011, 2016). The chapter contains six
figures showing similarity scores, word maps and a Zipfian distribution
illustrating her data. In this chapter, Bolognesi also takes up the topic of
Searle’s (1980) Chinese Room Argument, in which he imagines himself in a room
receiving messages in Chinese slipped under the door. He suggests that he can
answer these messages simply by manipulating the Chinese characters according
to certain rules, without learning or understanding Chinese. The question is
if this is what a computer does when it processes language and what the
relationship of the Chinese room is to the human brain.

Also in Chapter Seven, “Distributional models beyond language”, Bolognesi
discusses her own previous research (2014, 2017). The point of the research is
to acquire an understanding of associations between words and images.
Bolognesi studies Flickr® images and their tagsets in order to understand the
perceptual side of concepts. She is interested in what kind of features of
concepts are tagged by the users and how the concepts represented by Flickr®
data cluster. In this chapter, she also returns to world-to-world modelling,
describing, among other things, the challenges encountered by the MIT AI lab
in the seventies when they started working on computer vision. The chapter
ends with a summary of what has been discussed so far. The idea is that
Bolognesi will return to each topic thread in the third and last part of the
book. 

The title of the eighth chapter coalesces with the title of the entire book,
“Where words get their meaning”. The chapter starts from category formation,
which, as stated earlier in the book, occurs when a person associates an
object with another object, or an object with a word, or a word with another
word. Bolognesi underlines that this is also a cline of abstraction. This
inspires her to delve into the differences between concrete and abstract
concepts and eventually to return to L1 and L2 learning, the latter being more
language-based than the former. In this chapter, she discusses behavioral and
neuroscientific evidence related to abstract concepts and language learning.

In the next, ninth chapter, Bolognesi returns to distributional modelling. The
name of the chapter is “The cognitive foundations of the distributional
hypothesis”. Here, Bolognesi suggests that even if the human mind does not
function exactly like a computer program, successful computer modelling can
give us important insights about how the mind works. She says that we should
thus leave Searle’s Chinese room behind us and reach towards such insights.
She returns to the topic of abstraction and, quoting the APA Dictionary of
Psychology, suggests that there are at least two kinds of abstraction since
abstraction can refer both to categorical abstraction (specific to generic)
and conceptual abstractness. In the specific to generic type of abstraction we
infer common properties of, for example, tables, to arrive at a generic
understanding of what a table is. It is different from, for example, our
understanding of “goodness” or “beauty”. (VandenBos 2007.) Bolognesi is of the
opinion that metaphors can be understood in a similar way, as instances of
taxonomic categorization. She also applies the distributional hypothesis to
metonymy, and concludes that metaphors function in the domain of paradigmatic
similarity, while metonymy functions in the domain of syntagmatic contiguity.
Her main point in this chapter is that distributional modelling can help us
understand various kinds of meaning.  

In the tenth and last chapter “Conclusions and outlook” Bolognesi finally
brings together the topical threads that she has been handling throughout the
book. She again emphasizes that behavioral scientists can learn about the mind
through AI modelling and vice versa. She is of the opinion that we have
arrived at a point where it is necessary to consider both kinds of evidence.
In this chapter, she discusses human creativity, first language acquisition,
and foreign language teaching, pointing out what we can learn by marrying
behavioral sciences with AI research. Lastly, she predicts that we will
understand much more in the near future.

EVALUATION

On the outside, this book looks relatively thin, and when you read it, it is
deceptively simple. It is in fact a very intense book full of information. It
has been a challenge to attempt to summarize what it is about. On the one
hand, it is about how neural networks in AI can help us understand human
cognition. However, at the same time, it is about first and second language
learning. In her quest to combine insights from psycholinguistics and AI,
Bolognesi has to explain several complex issues in a rather limited space.
When she writes, for example, about world-to-world, word-to-world and
word-to-word associations, these are easy to imagine, but at the same time,
she continuously adds information that is more challenging to understand, such
as characteristics of computational modelling. She is quite deft at handling
the two and more threads of the work from the beginning to the end. The book
is like a plait where its author brings together linguistics (e.g. polysemy),
psycholinguistics (language acquisition) and AI (e.g. Latent Semantic
Analysis). Or, Bolognesi could be considered a juggler throwing several balls
in the air. The book is indeed built so that the author introduces or mentions
a topic, then moves on to another topic, then returns to a previous topic. It
is cumulative so that on each round, we learn something more about each topic.
It is also like a jigsaw puzzle where we are first introduced to one piece
after another, and then later see how they fit together, one by one.

The answer, then, to the question where words get their meaning, is at the
same time simple and complex. Word learning is equated with language learning
which occurs when the learners encounter new objects that have names, or texts
that include new words, and in the course of time learn to associate the right
words with the right referents, both on the basis of positive and negative
evidence. This general mechanism can be accounted for in relatively simple
terms but a further description of the process requires rigorous statistical
modelling. Also, not all words relate in the same way to other words but
somewhat different descriptions are required, for example, concerning metaphor
and metonymy. 

The main argument of the book, that we can understand where words get their
meaning if we combine insights from psycholinguistics and AI, is presented
boldly, and the author deserves credit for being able to maintain the simple
argument through all the complex issues she has dealt with in the book. At the
same time, I cannot escape the sense that there is still much to unveil in
these matters. The author herself points to a future where we will know more,
provided we walk the path she is suggesting. Perhaps this is just how a good
scientific book should end: the reader is left to wonder what more there is to
the matter. Curiosity has been roused. 

I can recommend this book to anyone who is interested in word meaning. It is a
well-researched book with plenty of references to further studies. It could
also work as an advanced course book at the university, compact as it is and
covers many relevant issues in a readable format. 

REFERENCES

Bolognesi, Marianna. 2011. Il lessico mentale bilingue e gli spazi semantici
distribuzionali: Le similarita’ tra verbi in L1, in L2 e nei corpora. Studi di
Glottodidattica 5(2). 51–72.

Bolognesi, Marianna. 2014. Distributional semantics meets embodied cognition:
Flickr® as a database of semantic features. In: Selected Papers from the 4th
UK Cognitive Linguistics Conference. 18–35. 

Bolognesi, Marianna. 2016. Metaphors, bilingual mental lexicon and
distributional models. In: Elisabetta Gola & Francesca Ervas (eds.) Metaphor
and Communication. Amsterdam: John Benjamins. 105–122. DOI:
10.1075/milcc.5.06bol

Bolognesi, Marianna. 2017. Flickr® distributional tag space: Evaluating the
semantic spaces emerging from Flickr® tag distributions. In: Michael N. Jones
(ed.) Big Data in Cognitive Science. London & New York: Routledge. 144–173. 

Kroll, Judith F. & Erika Stewart. 1994. Category interference in translation
and picture naming: Evidence for asymmetric connections between bilingual
memory representations. Journal of Memory and Language 33(2). 149–174. 

Rescorla, Robert A. 1988. Pavlovian conditioning: It is not what you think it
is. American Psychologist 43(3). 151–160.

Searle, John R. 1980. Minds, brains and programs. Behavioral and Brain
Sciences 3(3). 417–424.

VandenBos, Gary R. (ed.) 2007. APA Dictionary of Psychology (1st ed.).
Washington, DC: American Psychological Association.


ABOUT THE REVIEWER

Dr. Heli Tissari currently works as a university lecturer of English philology
at the University of Helsinki. Her own research mainly concerns English words
for emotions and their metaphors since Late Middle English, but she is also
more generally interested in the history of the English language, semantics
and cognitive linguistics, as well as interdisciplinary research. At the
moment, she is involved in a research project studying people’s reported
experiences of the music of digital games.





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