Emotion and sentiment analysis
Voci's speech scientists have applied machine learning techniques to the analysis of emotion and sentiment. Emotion information is extracted from the acoustic features of speech, while Sentiment is determined by analyzing the text generated from speech.
Computer models, trained using thousands of audio and text samples, are used to determine the emotion or sentiment of each utterance. Additional data indicate the words in the speech utterance that contribute to the computed sentiment. The separate emotion and sentiment values are then combined into a single Emotional Intelligence value that reveals the true voice of customers, so you can get to the heart of their concerns.
Since emotion and sentiment information is captured at the utterance level, Voci can determine how emotion is changing throughout the conversation, and whether the caller is in a more positive state at the end of the call than the beginning.
What are the differences between emotion and sentiment?
Sentiment and emotion are often used interchangeably, but are not the same. Emotion is a psychological state such as fear, anger, or happiness indicated by acoustic features of speech including pitch, speed, tone, and volume along with particular vocabulary used by the speaker that further helps to identify their emotional state.
Sentiment analysis only concerns specific vocabulary used by the speaker and does not take acoustic features of speech into account. Sentiment analysis looks for key words and phrases in a transcript such as "happy," "upset," "frustrated," "cancel," "hate," "angry," "thank you," “great," or “dislike” to evaluate the speaker's sentiment.
Enabling emotion analysis automatically enables sentiment analysis; however, emotion can also be disabled and sentiment analysis enabled separately. Refer to the following links for more information.
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