Abstract: An electronic device has pair(s) of conductive plates that is coupled to a housing and is electrically isolated by a dielectric material. The pair(s) of conductive plates is positioned to change relative orientation in relation to mechanical force that deforms the housing. Capacitive driver(s) is electrically coupled to pair(s) of conductive plates. A controller is communicatively coupled to the capacitive driver(s). The controller identifies a first capacitance of the pair(s) of conductive plates associated with the housing being in a normal state. The controller detects, via the capacitor driver(s), a change in capacitance from the first capacitance to a second capacitance of the pair(s) of conductive plates. The controller compares the change in capacitance to a threshold. In response to the change exceeding the threshold, the controller generates a notification.

Abstract: An electronic device includes a capacitive driver that is electrically coupled to a pair of conductive plates coupled to a housing and electrically isolated by a dielectric material. The conductive plates are positioned to change relative orientation in relation to deformation of the housing in a first direction. A controller identifies a first capacitance of the pair of conductive plates associated with the housing being in a normal alignment relative to the first direction. The controller presents an object on a user interface device in a first kinematic state. The controller detects, via the first capacitor driver, a change in capacitance from the first capacitance to a second capacitance of the pair of conductive plates. The controller associates the change to a first user input. The controller presents the object on the user interface device in a second kinematic state based on the first user input.

Abstract: An electronic device includes a capacitive driver that is electrically coupled to a pair of conductive plates coupled to a housing and electrically isolated by a dielectric material. The conductive plates are positioned to change relative orientation in relation to deformation of the housing in a first direction. A controller identifies a first capacitance of the pair of conductive plates associated with the housing being in a normal alignment relative to the first direction. The controller presents an object on a user interface device in a first kinematic state. The controller detects, via the first capacitor driver, a change in capacitance from the first capacitance to a second capacitance of the pair of conductive plates. The controller associates the change to a first user input. The controller presents the object on the user interface device in a second kinematic state based on the first user input.

Abstract: An electronic device has pair(s) of conductive plates that is coupled to a housing and is electrically isolated by a dielectric material. The pair(s) of conductive plates is positioned to change relative orientation in relation to mechanical force that deforms the housing. Capacitive driver(s) is electrically coupled to pair(s) of conductive plates. A controller is communicatively coupled to the capacitive driver(s). The controller identifies a first capacitance of the pair(s) of conductive plates associated with the housing being in a normal state. The controller detects, via the capacitor driver(s), a change in capacitance from the first capacitance to a second capacitance of the pair(s) of conductive plates. The controller compares the change in capacitance to a threshold. In response to the change exceeding the threshold, the controller generates a notification.

Abstract: An electronic device includes an audio synthesizer. The audio synthesizer can generate a voice-synthesized audio output stream as a function of one or more audible characteristics extracted from voice input received from an authorized user of the electronic device. The audio synthesizer can also apply an acoustic watermark to the voice-synthesized audio output stream, the acoustic watermark indicating that the voice-synthesized audio output stream is machine made.

Abstract: An electronic device includes an audio synthesizer. The audio synthesizer can generate a voice-synthesized audio output stream as a function of one or more audible characteristics extracted from voice input received from an authorized user of the electronic device. The audio synthesizer can also apply an acoustic watermark to the voice-synthesized audio output stream, the acoustic watermark indicating that the voice-synthesized audio output stream is machine made.

Abstract: An electronic device includes an audio synthesizer. The audio synthesizer can generate a voice-synthesized audio output stream as a function of one or more audible characteristics extracted from voice input received from an authorized user of the electronic device. The audio synthesizer can also apply an acoustic watermark to the voice-synthesized audio output stream, the acoustic watermark indicating that the voice-synthesized audio output stream is machine made.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: An electronic device includes an audio synthesizer. The audio synthesizer can generate a voice-synthesized audio output stream as a function of one or more audible characteristics extracted from voice input received from an authorized user of the electronic device. The audio synthesizer can also apply an acoustic watermark to the voice-synthesized audio output stream, the acoustic watermark indicating that the voice-synthesized audio output stream is machine made.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: A digital information encoder including a divider configured to divide a block of information into a plurality of sub-parts, an initial bit allocator configured to perform an initial allocation of bits to a KTH sub-part of said plurality of sub-parts, a processor configured to compute an estimated number of bits for encoding said KTH sub-part, and a bit allocation adjuster configured to obtain an adjusted bit allocation for said KTH sub-part by adjusting said initial allocation of bits to said KTH sub-part based, at least in part, on said estimated number of bits, wherein the encoder encodes said KTH sub-part using said adjusted bit allocation for said KTH sub-part.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Disclosed are systems and methods for the efficient conversion of linear predictive coefficients. This method is usable, for example, in the conversion of full band linear predictive coding (“LPC”) coefficients to sub-band LPCs of a sub-band speech codec. The sub-bands may or may not be down-sampled. In an embodiment, the LPC coefficients of the sub-bands are obtained from the correlation coefficients, which are in turn obtained by filtering the auto-regressive extended auto-correlation coefficients of the full band LPCs. The method also allows the generation of an LPC approximation of a pole-zero weighted synthesis filter.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.