731 results about "Emotion identification" patented technology

A method of predicting a mood state of a user may include recording an audio sample via a microphone of a mobile computing device of the user based on the occurrence of an event, extracting a set of acoustic features from the audio sample, generating one or more emotion values by analyzing the set of acoustic features using a trained machine learning model, and determining the mood state of the user, based on the one or more emotion values. In some embodiments, the audio sample may be ambient audio recorded periodically, and / or call data of the user recorded during clinical calls or personal calls.

An emotion recognition apparatus performs accurate and stable speech-based emotion recognition, irrespective of individual, regional, and language differences of prosodic information. The emotion recognition apparatus includes: a speech recognition unit which recognizes types of phonemes included in the input speech; a characteristic tone detection unit which detects a characteristic tone that relates to a specific emotion, in the input speech; a characteristic tone occurrence indicator computation unit which computes a characteristic tone occurrence indicator for each of the phonemes, based on the types of the phonemes recognized by the speech recognition unit, the characteristic tone occurrence indicator relating to an occurrence frequency of the characteristic tone; and an emotion judgment unit which judges an emotion of the speaker in a phoneme at which the characteristic tone occurs in the input speech, based on the characteristic tone occurrence indicator computed by the characteristic tone occurrence indicator computing unit.

The present invention relates to a dual-mode emotion identification method and system based on a facial expression and an eyeball movement. The method comprises a step of performing acquisition, a step of extracting a facial expression feature vector, a step of extracting an eyeball movement feature vector, a step of performing qualitative analysis on an emotional state, a step of performing matching-by-time and storage, a step of performing fusion and classification and a step of comparing emotional information. According to the method and system provided by the present invention, facial expression information of a to-be-tested object can be dynamically and accurately extracted and analyzed, and a correlation between the facial expression and the emotion is established; rich eye movement information can be accurately and efficiently acquired by means of tracking of an eye tracker, and the emotional state of the to-be-tested object is analyzed from the angle of the eyeball movement; and the facial expression feature vector and the eyeball movement feature vector are processed by using an SVR, so that the emotional state of the to-be-tested object can be obtained more accurately, and thus accuracy and reliability of emotion identification are improved.

The invention provides a method for extracting speech emotion information. The method is characterized in that speech data are acquired or transmitted by a mobile phone, a computer and a recording pen by virtue of a data acquisition or communication process, and the emotions of a speaker are identified by use of speaker unrelated and speaker related methods. The speaker unrelated emotion information extraction method adopted in the method for extracting speech emotion information is composed of two parts of speech database recording and speech emotion modeling, wherein the speech database recording part is taken as the reference for training an emotion identifier and comprises at least one emotion speech database; the speech emotion modeling part is used for establishing a speech emotion model as the emotion identifier. The accuracy rate of the speaker related emotion information extraction method adopted in the method for extracting speech emotion information can reach 80%, and the speaker related emotion information extraction method is used for identifying the emotions in a speech signal by adjusting internal parameters in a statistical manner. The method is capable of identifying other complex emotions by use of a group of special parameters describing basic emotions.