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The Unseen Tapestry: A Soul's Quest for Authentic Recognition

Updated: at 03:23 AM

With every beat of my heart, there is a story. Days are woven into weeks, months into years, threading the tapestry of my life with intricate patterns that never seem to emerge in conversations or fleeting glances between strangers fully. Today, I won’t blame the world for not trying to understand. After all, behind the everyday facade, there lies a narrative, a personal narrative that language often fails to capture.

Sometimes, I hear echoes of ’ Iris.’ The haunting melody of the Goo Goo Dolls sinks under my skin, unraveling threads of emotions buried deep within. Lyrics weave through my veins, touching places inside me that I never knew existed, giving voice to my longing—a longing that fills my soul to the brink, yearning for the comfort of a gaze that truly perceives.

The chorus reaches its crescendo—“I just want you to know who I am.”

The song isn’t merely about ‘exposing vulnerabilities’; it’s about the craving to share them, to have them held reverently in another’s hands, inspected, and understood in all their depth and complexity. I long for that connection—a soul resonance, to be deeply seen. Not just for the laughter and the courage I wear on my sleeve but for the fears that hide in the corners of my smile, the innocence that flees from the sharp corners of the world, and the hopes that painfully linger despite life’s relentless disappointments.

Why do I want this? It’s more than validation. It’s a yearning for acknowledgment that ‘these textures of my soul are real’, they exist, and aren’t just solipsistic impressions living in the silence of my heart.

I am more than my surface persona—more than the ordinary 32-year-old you see, always neatly dressed, the one who silently observes life with careful eyes and casually shrugs off heavy questions about love and life, labeling them as too philosophical or deep.

By piercing through the veil of everyday life, certain narratives that seldom find a voice emerge: stories of the lullabies that comforted me to sleep, the delightful thrill of the first summer rain, and the quiet tragedies that sculpted me through the years. A fierce sense of tenacity is concealed behind a steady gaze, with dreams incubating inside hollow nights and nurtured by a passion that refuses to bow before harsh realities.

Meeting me is like reading a book whose words are masks. Behind each carefully chosen expression, there are underlying chapters. Sometimes, I wish someone would commit to reading it, fondly yet resolutely turn the pages, making sense of the ‘abstract metaphors’, decoding the cryptic allusions, encountering the world that I am inside.

Every locked gaze feels like a chance for discovery, a possibility. I search for that mirrored recognition, an echo of my soul’s language in someone else’s eyes. It’s not merely about being seen; I want someone to look at me and say, “I see you, and I see myself. We’re the same.”

But until I find that recognition, until the words, ‘I see you’ are etched in someone’s gaze, I will continue painting my emotions on the ‘canvas of solitude’, carving my dreams on the stones of silence, longing for the day when someone shatters through the soundless echo of my solitary heart – wishing to truly understand, desiring to meet my eyes and see who I am, unmasked and unrestrained.

As ‘Iris’ echoes in the stillness, I’m left to hope that there’s a melody strong enough, a sight clear enough, a love brave enough, to discern the ‘true narrative of my life’.

import pandas as pd
import random

# Create a sample dataset
data = {
    'Narrative': [
        "I love listening to music.",
        "Music helps me express my emotions.",
        "I have endured a lot of pain in my life.",
        "I admire bravery in people.",
        "Persistence is the key to success."
    'Love_for_Music': [random.randint(1, 5) for _ in range(5)],
    'Depth_of_Emotions': [random.randint(1, 5) for _ in range(5)],
    'Pain_Endured': [random.randint(1, 5) for _ in range(5)],
    'Bravery': [random.randint(1, 5) for _ in range(5)],
    'Persistence': [random.randint(1, 5) for _ in range(5)],
    'Understood': [random.choice([0, 1]) for _ in range(5)]

# Create a DataFrame
sample_df = pd.DataFrame(data)

# Save the DataFrame to a CSV file
sample_df.to_csv('people.csv', index=False)
!pip install transformers

import nltk'vader_lexicon')

from transformers import RobertaModel, RobertaTokenizer
from nltk.sentiment.vader import SentimentIntensityAnalyzer
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import confusion_matrix, accuracy_score
from scipy import spatial
import pandas as pd
import torch

tokenizer = RobertaTokenizer.from_pretrained('roberta-base')
model = RobertaModel.from_pretrained('roberta-base')
sia = SentimentIntensityAnalyzer()

def get_roberta_embeddings(text):
    tokens = tokenizer.tokenize(text)
    encoded_input = tokenizer.convert_tokens_to_ids(tokens)
    attention_mask = torch.tensor([1]*len(encoded_input))

    with torch.no_grad():
        last_hidden_state = model(torch.tensor([encoded_input]), attention_mask = torch.tensor([attention_mask]))
    return last_hidden_state[0].numpy().mean(axis=1)

df = pd.read_csv('people.csv')
narratives = df['Narrative'].values
embeddings = []

for narrative in narratives:

df['Sentiment'] = df['Narrative'].apply(lambda narrative: sia.polarity_scores(narrative)['compound'])
df_emb = pd.DataFrame(embeddings)
df_features = pd.concat([df[['Love_for_Music', 'Depth_of_Emotions', 'Pain_Endured', 'Bravery', 'Persistence']], df_emb, df['Sentiment']], axis=1)

Y = df['Understood']
X_train, X_test, Y_train, Y_test = train_test_split(df_features, Y, test_size = 0.2, random_state = 42)

model = RandomForestClassifier(), Y_train)
Y_pred = model.predict(X_test)

cm = confusion_matrix(Y_test, Y_pred)
accuracy = accuracy_score(Y_test, Y_pred)

print('Confusion Matrix:')
print(f'Accuracy: {accuracy * 100}%')