Spoken opinion extraction for detecting variations in user satisfaction
In recent years, efforts have been made for automatically identifying opinions, emotions and sentiments in text. The problem considered in this paper is the analysis of messages uttered by the users of a telephone service in response to a recorded message that asks if a problem they had was satisfactorily solved. Very often in these cases, subjective information is combined with factual information. The purpose of this type of opinion analysis is the detection of time variations of user satisfaction indices. Even if precision or recall is not very high because messages are ambiguous or ASR systems have made many word recognition errors, system strategies are acceptable if they detect the same trend in user satisfaction as it is indicated by human interpreters of the messages. In this paper a system for this type of opinion analysis is proposed for a telephone service survey task.