Features, including one or more acoustic features, visual features, linguistic features, and physical features may be extracted from signals obtained by one or more sensors with a processor. The acoustic, visual, linguistic, and physical features may be analyzed with one or more machine learning algorithms and an emotional state of a user may be extracted from analysis of the features. It is emphasized that this abstract is provided to comply with the rules requiring an abstract that will allow a searcher or other reader to quickly ascertain the subject matter of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims.

Multi-modal sensor based emotion recognition and emotional interface

A speech recognition method, medium, and system. The method includes detecting an energy change of each frame making up signals including speech and non-speech signals, and identifying a speech segment corresponding to frames that include only speech signals from among the frames based inclusive of the detected energy change.

Speech detection method, medium, and system

A signal manipulator for manipulating an audio signal having a transient event may comprise a transient remover (100), a signal processor (110) and a signal inserter (120) for inserting a time portion in a processed audio signal at a signal location where the transient event was removed before processing by said transient remover, so that a manipulated audio signal comprises a transient event not influenced by the processing, whereby the vertical coherence of the transient event is maintained instead of any processing performed in the signal processor (110), which would destroy the vertical coherence of a transient.

Device and method for manipulating an audio signal having a transient event

An apparatus having a voice-estimation (VE) interface that probes the vocal tract of a user with sub-threshold acoustic waves to estimate the user' s voice while the user speaks silently or audibly in a noisy or socially sensitive environment. In one embodiment, the VE interface is integrated into a cell phone that directs an estimated-voice signal over a network to a remote party to enable (i) the user to have a conversation with the remote party without disturbing other people, e.g., at a meeting, conference, movie, or performance, and (ii) the remote party to more- clearly hear the user whose voice would otherwise be overwhelmed by a relatively loud ambient noise due to the user being, e.g., in a nightclub, disco, or flying aircraft.

Voice-estimation interface and communication system

Emotion recognition may be implemented on an input window of sound. One or more auditory attention features may be extracted from an auditory spectrum for the window using one or more two-dimensional spectro-temporal receptive filters. One or more feature maps corresponding to the one or more auditory attention features may be generated. Auditory gist features may be extracted from feature maps, and the auditory gist features may be analyzed to determine one or more emotion classes corresponding to the input window of sound. In addition, a bottom-up auditory attention model may be used to select emotionally salient parts of speech and execute emotion recognition only on the salient parts of speech while ignoring the rest of the speech signal.

Emotion recognition using auditory attention cues extracted from users voice

A method of reducing noise in an audio signal, comprising the steps of: using a furrow filter to select spectral components that are narrow in frequency but relatively broad in time; using a bar filter to select spectral components that are broad in frequency but relatively narrow in time; analyzing the relative energy distribution between the output of the furrow and bar filters to determine the optimal proportion of spectral components for the output signal; and reconstructing the audio signal to generate the output signal. A second pair of time-frequency filters may be used to further improve intelligibility of the output signal. The temporal relationship between the furrow filter output and the bar filter output may be monitored so that the fricative components are allowed primarily at boundaries between intervals with no voiced signal present and intervals with voice components. A noise reduction system for an audio signal.

Audio spectral noise reduction method and apparatus

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Audio spectral noise reduction method and apparatus