• Riddhisha Srivastava
• Anurag Shrivastava
• Sachin Tripathi
• Anshika Mishra
• Ishaan Tripathi

Decoding the tone involved and conveyed through any piece of text is one such difficult task because of sarcasm and irony. This paper proposes Tone Tracer: an intelligent analytical tool that can decode the tone conveyed through any piece of written text by identifying the tone involved. This analytical tool utilizes natural language processing algorithms and machine learning algorithms to identify whether any piece of text contains sarcasm or not. Different pre-processing techniques such as tokenization, removal of stop words, and TF-IDF feature evaluation are involved to enhance accuracy. This analytical tool involves the use of logistic regression algorithms because of their efficiency. This analytical tool has been implemented by developing an interactive interface that can analyze any piece of text. Experimental analysis reveals that Tone Tracer can identify the tone involved and enhance accuracy. This research work has numerous applications in areas such as analyzing emotions through any piece of text.

Sarcasm Detection, Context-Aware Learning, Transformer Architecture, Natural Language Processing, Conversational Analysis

"Tone Tracer: Decoding The Hidden Meaning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 1, page no.a490-a494, January-2026, Available :http://www.jetir.org/papers/JETIR2601060.pdf

"Tone Tracer: Decoding The Hidden Meaning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 1, page no. ppa490-a494, January-2026, Available at : http://www.jetir.org/papers/JETIR2601060.pdf