Data processing: speech signal processing – linguistics – language – Speech signal processing – Application
Reexamination Certificate
1999-08-31
2001-08-14
Dorvil, Richemond (Department: 2641)
Data processing: speech signal processing, linguistics, language
Speech signal processing
Application
C704S270000
Reexamination Certificate
active
06275806
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to voice recognition and more particularly to detecting emotion using statistics calculated for voice signal parameters.
BACKGROUND OF THE INVENTION
Although the first monograph on expression of emotions in animals & humans was written by Charles Darwin in the last century and psychologists have gradually cumulated knowledge in the field of emotion detection and voice recognition, it has attracted a new wave of interest recently by both psychologists and artificial intelligence specialists. There are several reasons for this renewed interest: technological progress in recording, storing and processing audio and visual information; the development of non-intrusive sensors; the advent of wearable computers; and the urge to enrich human-computer interface from point-and-click to sense-and-feel. Further, a new field of research in AI known as affective computing has recently been identified.
As to research on recognizing emotions in speech, on one hand, psychologists have done many experiments and suggested theories. On the other hand, AI researchers made contributions in the following areas: emotional speech synthesis, recognition of emotions and using agents for decoding and expressing emotions. Similar progress has been made with voice recognition.
In spite of the research on recognizing emotions in speech, the art has been devoid of methods and apparatuses that utilize emotion recognition and voice recognition for business purposes.
SUMMARY OF THE INVENTION
A system, method and article of manufacture are provided for detecting emotion using statistics. First, a database is provided. The database has statistics including statistics of human associations of voice parameters with emotions. Next, a voice signal is received. At least one feature is extracted from the voice signal. Then the extracted voice feature is compared to the voice parameters in the database. An emotion is selected from the database based on the comparison of the extracted voice feature to the voice parameters and is then output.
In one aspect of the present invention, the feature that is extracted includes a maximum value of a fundamental frequency, a standard deviation of the fundamental frequency, a range of the fundamental frequency, a mean of the fundamental frequency, a mean of a bandwidth of a first formant, a mean of a bandwidth of a second formant, a standard deviation of energy, a speaking rate, a slope of the fundamental frequency, a maximum value of the first formant, a maximum value of the energy, a range of the energy, a range of the second formant, and/or a range of the first formant.
In another aspect of the present invention, the database includes probabilities of a particular voice feature being associated with an emotion. Preferably, the selection of the emotion from the database includes analyzing the probabilities and selecting the most probable emotion based on the probabilities. Optionally, the probabilities of the database may include performance confusion statistics. Also optionally, the statistics in the database may include self-recognition statistics.
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Andersen Consulting LLP
Armstrong Angela A.
Dorvil Richemond
Oppenheimer Wolff & Donnelly LLP
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