The project, initially conceived in 2008, began as a visual-linguistic exploration titled ‘Chromatophonography.’ It aimed to research and visualize the musicality inherent in the ghazals of the renowned Iranian poet, Hafiz. During its early phase, colored maps were created for a selection of Hafiz’s ghazals using an innovative method. Notably, two of these maps were presented at the 44th Notre Dame Poetry Festival.
Years later, the project underwent significant development. Through continued research into the music of poetry and the expansion of the initial concept—which involved utilizing the pronunciation wavelengths of Persian consonants and vowels, mapping them to a previous color table, applying syllables* with color gradients, and generating tone noises for audio purification of the poetry’s music—the visualizations evolved. The maps became more complex and precise, transitioning from conventional representations to the encoding of physical information. Subsequently, these maps became translatable through light and sound installations.
Fundamentally, this project serves as a form of phonography and a method for extracting the inherent music of Persian rhythmic poetry, approached through a formalist lens that prioritizes poetry and its language as a multimedia art form.
The project has since been renamed ‘The Invisible Tablet.’ This new title, inspired by Hafiz’s multifaceted use of the word ‘tablet’ (as in ‘simple tablet,’ ‘tablet of vision,’ ‘silver tablet,’ ‘tablet of chest,’ etc.), alludes to the hidden layer of aesthetic experience within Hafez’s ghazals. This aesthetic dimension is linguistically untranslatable and can only be truly apprehended through the illuminating power of art.
“You said Hafiz! What are all these colors and imaginations? Don’t see the wrong motifs! We are just a simple tablet.”**
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*A syllable in Persian is a continuous sound string that consists of one vowel and one to three consonants. The meaning of the constant phonetic sequence is that the syllable-forming components produced a production process without a pause.
Q-365
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Knowledges
Acoustic Characteristics
The four fundamental properties of sound are:
Syllabic Structure in Persian
A syllable in Persian is a continuous string of sounds consisting of one vowel and one to three consonants. Syllable formation is a production process occurring without a pause.General Formulas:If we use C for Consonants and V for Vowels, and place optional units in parentheses, we can define the syllabic
Persian: CV(C)(C)
A Persian syllable always begins with a consonant, followed immediately by a vowel.
English: (C)(C)(C)V(C)(C)(C)(C)
Vowels in Persian:
There are six vowels in Persian:
Pattern CV (with a short vowel) e.g., /ke/ (that)
Pattern A: CV (with a long vowel), e.g., /bā/ (with) Pattern B: CVC (with a short vowel), e.g., /del/ (heart)
Classification by Ending:
The number of “overlong” (drawn) syllables in a line affects the internal music. As the number of these syllables increases relative to the metrical pattern, the rhythm becomes “heavier.”
If two lines share the same meter and rhyme but differ significantly in the number of overlong syllables, their internal musical texture changes, sometimes making it difficult to recognize that they share the same meter.
Example from Hafez: The following couplet contains a high frequency of overlong syllables (seven in total), creating a heavy, distinct rhythm:
hāfezčoraftrūzevogolnīzmīravadnāčārbādenūškeazdastraftkār
(Translation: Hafez, since the fast has departed and the rose is also leaving / You must drink wine, for the opportunity is slipping away.)
CV: CVC CV CVCC CV: CV CV CVC CV:C CV: CV CVC CV: CV:C CV: CV CV:C CV CV CVCC CVCC CV:C
References:
Methodology: Mapping Persian Phonemes to Light & Sound
I have assigned a theoretical physical wavelength (in meters) to each Persian consonant and vowel. Using the speed of sound in air at 20°C (approx 343 m/s), I calculated the corresponding
frequency (Hz) for each phoneme.
The Logic of Assignment: The mapping reflects linguistic sonority. Vowels are treated as “longer” waves (lower frequency/higher resonance), while consonants are treated as “shorter” waves (higher frequency).
Conceptual Note: This is a consistent conceptual model designed for sonification and visualization purposes. It does not aim to replicate the complex spectrographic reality of human speech, where phonemes consist of multiple formants rather than single pure tones.
the physical mapping is acoustically accurate. I merged these graphemes so that each unique sound corresponds to a single wavelength.
Consolidated Phoneme Groups:
/s/: Includes: س (Sin), ث (Se), ص (Sād)
/z/: Includes: ز (Ze), ذ (Zal), ض (Zād), ظ (Zā)
/h/: Includes: ه (He), ح (Hā)
/t/: Includes ت (Te), ط (Tā)
Note on Dialects: In Standard Iranian Persian, غ (ghayn) and ق (Qaf) are merged. However, in other dialects (e.g., Dari or Classical Persian), ق is realized as a voiceless uvular stop [q], distinct from غ. This model primarily follows the classic pronunciation.
The “Red Shift” Challenge: A direct linear mapping of acoustic wavelengths to the visible light spectrum poses a problem: The acoustic range is wide, while the visible spectrum is narrow. Consequently, a direct translation causes most mapped colors to cluster at the “long wavelength” end of the visible spectrum (Deep Red).
To achieve a distinct and aesthetic color palette, I applied a non-linear transformation.
Logarithmic Mapping: Frequencies are mapped logarithmically (rather than linearly) to match human perception of pitch.
HSV Space: Instead of converting directly to visible nanometers, I mapped the acoustic frequencies to Hue in the HSV (Hue, Saturation, Value) color space. This approach ensures a wider hue spread across the spectrum, allowing the visualization to move beyond red tones and represent the full diversity of the phonemes.
synesthesia
It is important to distinguish this project’s approach from synesthesia and specifically its subtype, Chromesthesia (Sound-to-Color Synesthesia), which is a neurological phenomenon where stimulation of one sensory pathway leads to automatic, involuntary experiences in another. For example, a person might inherently ‘see’ the sound of a specific vowel or the note ‘C’ as red. However, synesthesia is subjective and varies wildly between individuals.
This project does not rely on subjective perception. Instead, it establishes a deterministic physical relationship based on wave physics. While color is how the eye interprets light frequency, and pitch is how the ear interprets sound frequency, this model uses a mathematical bridge to translate one scale to the other. It creates a consistent, universal visualization logic rather than replicating a personal psychological experience.
Color of Noise
The term “color” is used in acoustics to describe different types of noise based on their frequency content.
Both light (color) and sound are types of waves, but they are fundamentally different. Light is both light (color) and sound are types of waves, but they are fundamentally different. Light is an electromagnetic wave, while sound is a mechanical wave that travels through a medium like air. An electromagnetic wave, while sound is a mechanical wave that travels through a medium like air.
Project Scope and Scalability
This presentation serves as a small-scale prototype of a more comprehensive research initiative currently under development. The broader project is expanding along two distinct axes: quantitatively, by scaling the analysis to encompass a larger corpus of the Qazals; and qualitatively, by refining the acoustic algorithms and enhancing the fidelity of the sensory translation methods, utilizing more technology.
