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Welcome to the Textones Project.
-Modeling For the Inquiring Mind- This page contains the first generation of Textone Modeling. For the most recent model, click here: Second Generation of Modeling Sonnet 18 |
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Why Model Literature? At the root of all literary interpretation, and, possibly, all literature, is a desire for increased understanding of the human condition. Once, it may have been enough to understand a protagonists actions based on the character’s emotional or moral state, the main consideration being that motivation was housed within these spheres. Today, there is an ever-growing awareness that cognitive functioning plays a major role in human behavior, and the awareness of the analyst must grow accordingly. To some extent, this may require a distancing by the analyst/modeler from a narrative in order to facilitate objectification of a work. This distance can be achieved via modeling because, to some extent, modeling removes the subjective element inherent in literary analysis; it is hoped an empirical type of effect can be achieved in modeling that is biased towards the quantitive as a means of exposing the qualitive. |
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Why Audio Modeling? Audio modeling of a literary work is not new. Texts have been applied to music for centuries in operatic interpretations. However, the Textones concept of tonal modeling is that tones should be applied directly to parts of speech in a mechanical fashion, rather than in typical, musical fashion, music being designed with only aesthetics in mind; musicality was not an early consideration of the Textones concept. The more important goal was the discovery of possible recurring patterns within speech that would indicate universalities in language construction among writers of literary works, and, therefore, possible universalities in cognition. However, the Textone Project clearly recognizes that music creates concordance of thought where text fails--after all, music, like love, is a universal language--and with this in mind, musicality has become an important factor in the Textones listening process; ultimately, we may be trading close reading for close listening. |
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Consistency. The initial question facing the Textones Project was whether tones could be applied to text in a way that would produce consistent results. While it might be easy to assign tonal values to one sonnet in order to make it sound interesting, a mechanism was sought which could be applied repetitively, thereby revealing traits within a variety of literary works and raising quantitative modeling across genres. A key idea behind Textones is that, while assignment of tones to parts of speech may be subjective, as long as assignations are consistent, results will be non-subjective; texts are not being interpreted in regard to their emotive context; the language retains its mechanical function and the tones merely indicate language structure employed by the writer. |
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Subjectivity and Close Reading. Recent modeling methods reveal something interesting about literary close reading analysis; close reading is a personal, individual system of modeling inspired by emotional responses of the modeler to the work. Those responses are then mentally interpreted via a secondary, mental process. In close reading, we are often asked to analyze why a certain text produces a certain feeling or result in the reader—in effect, we are asked to read between the lines. In Textones modeling, however, we seek to read only the lines. The hope is to ignore the emotive, believing it can hinder an understanding of the mechanical functioning of a text, and this in turn may lead to an obscuring of the larger scope of a work. In addition, Textones modeling is based on the idea that mechanical functioning is of greater importance in the initial comprehension of a work, mechanics within a work being a reflection of the artist's cognitive function, and that mechanical diagrams might be considered as a canvas upon which other analysis is then laid out in an attempt to balance content with form. |
First Generation Modeling of Sonnet 18
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The Story So Far: Sonnet XVIII was parsed into parts of speech and tonal values were assigned (below left). These tonal values were plotted on a chart (below right) to prepare for input into a tonal sequencer (Protools). Being a first attempt, this model indicates a method or system, albeit a preliminary one. A more complex system is in progress which acknowledges phrases as parts of speech as well as individual words. |
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Legend: |
Sonnet 18
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Syllables and BPM. In an attempt to explore the parallel between meter in verse and rhythm in music, tonal values have been sequenced in relation to the number of syllables in each word. For example, the word "eternal," being three syllables, occupies three beats in a ten beat line of pentameter. Not all Shakespeare's sonnets have perfect pentameter on each line, but Sonnet 18 does. Furthermore, there is a two beat pause at the end of each line in mimicry of pauses taken between lines. Tone Lengths. In any sentence or verse, we cannot be sure of its meaning until we determine its ending. To amplify this thought, we also understand that one word will color or modify another word, as in, "the black cat." By acknowledging each word's ability to modify another word, textones are layered, resulting in multi-tonal voicings. This system works as follows: any adjective-tone occurring immediately before a noun-tone is held until the noun-tone ends, thus "coloring" the noun-tone in the same way an adjective colors a noun in text. Likewise, a verb-tone is held to color the object it acts upon.
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| Hear the Results So Far: (It is suggested you read the text at the same time you listen to the Textone.) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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The Challenge This fanciful diagram depicts the ultimate Textones Machine. Assuming we could configure these various software applications within one computer, the result would be somewhat akin to synethsesia; colored lights glowing as audio-textual analysis occurs. Text would be input into a parts-of-speech parser, and from one output channel, the creation of midi triggers would correspond to parts of speech in the text. These midi triggers would then fire pre-assigned tones. The parser's second output channel would highlight corresponding parts of text; ie. as a noun tone is heard, all nouns within the text would light up (this idea from Jeremy Douglass at UCSD). In addition, this project attempts to understand cognitive function in the brain. The brain differentiates between music and text; one is heard, the other is read. Therefore, a model might be of interest that highlights images of specific brain areas responding to language and/or music as Textones play. Complexities of Language When young, we are taught to think of individual words as having individual meanings that we then join together to make a sentence which represents a mental stringing of symbols and images. We also recognize that words can either be "form words" (nouns, verbs, adjectives, adverbs) or "structure words" (prepositions, conjunctions, articles) (citation pending). However, beyond this, language works on several different levels simultaneously. Meaning inherent in one word is retained and carried over to subsequent words, as in "the black cat." "The" denotes specificity, and "black" imbues the noun "cat" with a value, in this instance a color value. So it is with a prepositional phrase. Shakespeare's "darling buds" are "of May," and here, "May" is neither subject nor object; it merely describes the buds. Also caught up in that phrase is "of." It becomes clear that, even in the simple phrase, "Rough winds do shake the darling buds of May," the mind has to connect "Rough" with "May," and interpret the value of "May" as being a lesser value than the nouns "winds" or "buds." It must also apply "May" to the buds only for the reader to gain the sense that something is amiss, for does one not get the feeling that the "Rough winds" are combative toward the buds? The relationship between "buds" and "May" has import because buds do not appear in December, and if they did, the rough winds would seem appropriate to the season and tension would be lost. Furthermore, the buds are "darling," precious, not to be roughed up by winds. Tension is generated due to the contrast between "Rough" and "darling." Clearly, language is complex in ways we take for granted on a daily basis. Limitations Therefore, the big trick in all of this is to come up with a parser that can decipher and label not only subject, verb, direct object, indirect object, adjective, adverb, article, conjunction, and preposition, but prepositional phrases which include nouns that are neither subject, nor direct object, nor indirect object. Unfortunately, this parser seems a little way off yet, as the most advanced parsers available can detect basic parts of speech within individual words, and even subjects and objects (which they may do simply by determining the first and second nouns in a sentence), but not prepositional phrases which may take a great deal more computational flexibility. (The lack of capitalization here identifies "may" as the adverb, "possibly.") The Binomial Brain Like digital computation, the brain is binomial in function. Just as computer data is represented by a toggling of zeroes and ones, (off, on), so too do the synaptic nerves fire. They do not fire partially. Due to chemical inhibitors, discharge across a synapse is achieved fully or not at all; it is an "on, off" function. (citation pending). We might say, then, that all human knowledge is managed and communicated through a myriad series of binomial actions. Little wonder that we turn to digital media as a way on enhancing our personal knowledge base further; we are intimately familiar with its logic. In this light, the marriage between digital transmission of information and literature seems more than appropriate: if literature is a result of binary brain function, the binary code used in digital computation could be seen as a literal extension of the human brain. The question is: Can digital computation develop creativity? This question has been posed within the concept of Artificial Intelligence and no longer seems an impossibility. An advanced parser may need to be creative to function comprehensively. |
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The Joy of Parsing. Parsing a Shakespearean sonnet can prove challenging. Linguists and literary analysts debate "meaning" in language, and, possibly, no where is this more evident than when dealing with the works of Shakespeare, where meaning may become fluid. Taking into account that 16th century English was used in a different fashion than it is today, and considering Shakespeare's evident pleasure in the creation of complex syntax and meaning, parsing many of his sonnets entails considerable research. An Exhaustive
Analysis of Language Use in Sonnet 18 Sonnet 18 Converted to Normal Word Order Sentences (Subject Verb Object)
Construction Type *
NOTE:
There
could be a case made for dividing these four lines into two
sentences of two lines each, COMPOUND & COMPOUND/COMPLEX
respectively, and using the "But" as a "However." 1. Shall I compare thee to a summer's day? Interrogative I
| shall compare thee
to a summer's day? 2. Thou art more lovely and more temperate: Declarative Thou |
art more lovely and more temperate. 3. Rough winds do shake the darling buds of May, / And summer's lease hath all too short a date: Declarative Rough winds |
do shake the darling buds of May and
summer's lease | hath
all too short a date. 4. Sometime too hot the eye of heaven shines, / And
often is his gold complexion dimm'd;
Declarative The eye of heaven | sometime shines
too hot, and his gold complexion | often
is dimm'd,
and every fair |
sometime
declines from fair, untrimm'd by chance or
[by] nature's changing course, but thy
eternal summer | shall
not fade nor lose possession of that
fair [that] thou
| owest, NOTE:
[that]
= that fair nor Death | shall brag
[that] thou | wander'st in his shade
when thou | growest in eternal lines to
time. |