Analysis of Voice Cues in Recognition of Sarcasm

Background: The voice recognition system is about cognizing the signals, by feature extraction and identification of related parameters. The entire process is referred to as voice analytics. Objective: The paper aims at analyzing and synthesizing the phonetics of voice. The work focuses on the facts of voice analytics i.e. basic blocks of ‘Glottal signature’. The glottal signature and unique voice cues are evaluated to derive the relationship for utterance of emotional words which leads to sentimental expression cues. An effort is made to map further to understand sarcasm behavior in the sounds made by human speech. Methods: The basic blocks of unique features identified in the work are Intensity, Pitch, Formants related to speak, read, interactive and declarative sentences solely on voice cues not on linguistic theory. It is also tested to identify derived features that maps to fine-grained details of voice cues to drill up usage in sarcasm detection. Results: Different unique features identified in the work are, intensity, pitch, formants related to read, speak, interactive and declarative sentences and derived parameters. Conclusion: The work carried out in the paper also supports the analysis of voice segmentation labelling, analyzes the unique features of voice cues, understanding physics of voice, the process is further carried out to recognize sarcasm.