Voice sentiment analysis is concerned with quantifying affective state based on what type of features?
Answer
Paralinguistic features embedded in the sound wave itself
Voice sentiment analysis focuses on extracting and interpreting non-verbal acoustic features directly from the audio signal, such as pitch, volume, and speech rate, which are classified as paralinguistic features.
Related Questions
Voice sentiment analysis coalesced from advancements in which two primary technological disciplines?What characterized early approaches used in textual sentiment analysis?What were the primary focuses of early speech analytics technology?What critical understanding signaled the need to move beyond mere transcription in voice analysis?Voice sentiment analysis is concerned with quantifying affective state based on what type of features?Which acoustic measurement is defined as the irregularity in pitch?Which spectral feature models the short-term power spectrum of a sound to effectively capture timbre or quality?What analytical observation describes the fundamental shift in approach between text sentiment and voice sentiment analysis?Features like fundamental frequency (pitch contours), speaking rate, and pauses fall under which acoustic feature domain?Which statistical models were explored in early academic probes for building predictive classification models based on extracted acoustic features?What is the key difference in the data analyzed by Voice Sentiment Analysis compared to the output of historical Speech Analytics?