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Communicating across voice and text channels with emotion preservation

Emotion across voice and text communication channels are abstracted, preserved and translated. A voice communication is received and analyzed for emotion content. The textual content of the communication is realized summarily using word recognition techniques. The textual content is then analyzed for emotion content. Words and phrases derived from the word recognition are compared emotion words and phrases in a text mine database. The emotion from the two analyses is then used for marking up the textual content as emotion metadata. The text and emotion markup abstraction for a voice communication can also be translated into a using text and emotion translation definitions. The translated emotion metadata is used to emotion mine words that have an emotion connotation in the culture of the second language. Those words are then substituted for corresponding words in the translated text. The translated text and emotion words are modulated into a synthesized voice and the delivery is adjusted using emotion voice patterns derived from the translated emotion metadata. Additionally, text and emotion markup abstractions can be archived as artifacts of their original voice communication and then be searched using emotion conditions for the context of the original communication. A search query includes for communication artifact includes an emotion value and a context value that are used to sort the database artifacts. Result artifacts that contain matching emotion metadata, within the context constraint, are passed to the requestor for review.
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