1. A method for automatically detecting sentiments in an audio signal of an interaction held in a call center, comprising: receiving the audio signal from a logging and capturing unit associated with the call center; performing audio analysis on the audio signal to obtain text spoken within the interaction; segmenting the text into context units according to acoustic information acquired from the audio signal to identify units of speech bound by non-speech segments; wherein each context unit includes one or more words; extracting a sentiment candidate context unit from the context units using a phonetic based search; extracting linguistic features from the text of the sentiment candidate context unit and acoustic features from a segment of the audio signal associated with the sentiment candidate context unit; determining in accordance with the linguistic features and acoustic features whether the sentiment candidate context unit is valid or erroneous; and determining sentiment polarity and intensity for the sentiment candidate context unit.