Classification Methodology

This page explains how the analyzer computes varna and matra details, then maps the observed pattern to a chhand classification.

1) Input Normalization

The analyzer accepts Devanagari Sanskrit input and normalizes spacing. Vedic accent marks are removed for metrical counting consistency.

2) Segmentation (Split View)

Input is segmented by danda symbols and line breaks. Each segment is treated as a pada candidate. The exact split is shown in output for transparency.

3) Akshara Parsing

Each word is parsed into aksharas using consonant clusters, vowel signs, and modifiers. Trailing consonant behavior and conjunct effects are applied to derive guru/laghu weight.

4) Matra and Varna Computation

For each analyzed pada:

• Varna: count of akshara units used for varna-based meter mapping.
• Matra: per-akshara weight shown as laghu (1) or guru (2).

Both are displayed so users can audit the result.

5) Chhand Mapping

The observed varna pattern (example: 8-8-8-8) is compared against modeled patterns such as:

• Gāyatrī (गायत्री): 8-8-8
• Uṣṇih (उष्णिह): 8-8-12
• Anuṣṭubh (अनुष्टुभ): 8-8-8-8
• Bṛhatī (बृहती): 8-8-12-8
• Paṅkti (पङ्क्ति): 8-8-8-8-8
• Triṣṭubh (त्रिष्टुभ): 11-11-11-11
• Jagatī (जगती): 12-12-12-12

The top match is returned with confidence and rationale. Additional candidates are shown for ambiguity handling.

6) Timeout UX Rule

If analysis exceeds 10 seconds, the UI displays:

It has taken more than 10 seconds. Please contact ino@kotibyte.com for further support.