Abstract: Pancake mixes comprising at least one type of whole grain flour, at least one natural sweetener, at least one fat and a leavening system are provided herein. Packaged food products comprising single-serving containers containing said pancake mixes, as well as methods of preparing pancakes, are also provided. The pancakes described herein are preferably 100% whole grain and free from preservatives and/or artificial colorings.

Abstract: An electronic device includes a microphone that receives an audio signal that includes a spoken trigger phrase, and a processor that is electrically coupled to the microphone. The processor measures characteristics of the audio signal, and determines, based on the measured characteristics, whether the spoken trigger phrase is acceptable for trigger phrase model training. If the spoken trigger phrase is determined not to he acceptable for trigger phrase model training, the processor rejects the trigger phrase for trigger phrase model training.

Abstract: A method and apparatus increase audio output of a device. A mode of audio output operation of a device can be determined. Audio output can operate in a determined first mode of audio output operation that powers at least one first speaker at a first bandwidth and at a first output level below a first output level threshold. The audio output can operate in a determined second mode of audio output operation. The second mode of audio output operation can power the at least one first speaker at a high pass filtered second bandwidth that filters out low frequencies of the first bandwidth. The second mode of audio output operation can power the at least one first speaker at a second output level below a second output level threshold. The second output level threshold can be higher than the first output level threshold. The second output level can exceed the first output level threshold at least once.

Abstract: Voice controlled multimedia content creation techniques are discussed in which a multimedia package is created and shared to a specified destination responsive to voice commands. The voice commands can be received by a device as a single stream (e.g., a single phrase) that causes automatic performance of a sharing sequence or as a series of multiple voice commands that are input in response to prompts for voice input as part of the sharing sequence. The voice commands can be recognized and handled by a content creation system of the device to select a clip for tagging of content (such as captured audio or video). The selected clip is then combined with the content to create the multimedia package. Voice commands can also be employed to specify a destination for sharing of the content, such as one or more contacts or a particular sharing site.

Abstract: An electronic device includes a microphone that receives an audio signal that includes a spoken trigger phrase, and a processor that is electrically coupled to the microphone. The processor measures characteristics of the audio signal, and determines, based on the measured characteristics, whether the spoken trigger phrase is acceptable for trigger phrase model training. If the spoken trigger phrase is determined not to be acceptable for trigger phrase model training, the processor rejects the trigger phrase for trigger phrase model training.

Abstract: A method and apparatus for voice recognition performed in a voice recognition block comprising a plurality of voice recognition stages. The method includes receiving a first plurality of voice inputs, corresponding to a first phrase, into a first voice recognition stage of the plurality of voice recognition stages, wherein multiple ones of the voice recognition stages includes a plurality of voice recognition modules and multiples ones of the voice recognition stages perform a different type of voice recognition processing, wherein the first voice recognition stage processes the first plurality of voice inputs to generate a first plurality of outputs for receipt by a subsequent voice recognition stage. The method further includes, receiving by each subsequent voice recognition stage a plurality of outputs from a preceding voice recognition stage, wherein a plurality of final outputs is generated by a final voice recognition stage from which to approximate the first phrase.

Abstract: Configuring an adaptive microphone array to gather signals from a main lobe of the array, and configuring the array to reduce side interference gathered from sources that are not situated within the main lobe. A memory stores test signals gathered by the array at a plurality of predetermined angular bearings with reference to the array in an anechoic chamber. Signals gathered in real time are processed to provide a preliminary output and preliminary weights. The test signals are retrieved from memory. The preliminary weights are applied to the test signals to provide null steering weights. The null steering weights and the preliminary output are processed to reduce or minimize the amplitude response of the array at the angular orientation.

Abstract: An electronic device includes a microphone that receives an audio signal, and a processor that is electrically coupled to the microphone. The processor detects a trigger phrase in the received audio signal and measure characteristics of the detected trigger phrase. Based on the measured characteristics of the detected trigger phrase, the processor determines whether the detected trigger phrase is valid.

Abstract: An apparatus includes a group of microphones and a surface compensator that is operatively coupled to switch logic and to a signal conditioner that provides a control channel to voice recognition logic. The surface compensator may detect surfaces in proximity to the apparatus as well as the surface's acoustic reflectivity or acoustic absorptivity and may accordingly configure the group of microphones including selecting appropriate signal conditioning and beamforming based on the surface acoustic reflectivity or acoustic absorptivity and the orientation of the apparatus. Voice recognition performance is thus improved when microphones are impeded or occluded by proximate surfaces. A group of sensors of the apparatus is used by the surface compensator to detect surfaces and surface type, and to determine apparatus orientation and motion.

Abstract: A method includes detecting a surface in proximity to a mobile device using sensor data and determining an acoustic reflectivity or acoustic absorptivity of the surface using the sensor data. The method may further compensate for the acoustic reflectivity or acoustic absorptivity by controlling a configurable group of microphones of the mobile device. Compensating for the surface acoustic reflectivity or acoustic absorptivity may include beamforming the outputs of the configurable group of microphones to obtain one of an omnidirectional beamform pattern or a directional beamform pattern. An apparatus that performs the method include a configurable group of microphones, a signal conditioner, and a surface compensator. The surface compensator is operative to detect a surface in proximity to the apparatus and determine a surface acoustic reflectivity or acoustic absorptivity.

Abstract: An electronic device digitally combines a single voice input with each of a series of noise samples. Each noise sample is taken from a different audio environment (e.g., street noise, babble, interior car noise). The voice input/noise sample combinations are used to train a voice recognition model database without the user having to repeat the voice input in each of the different environments. In one variation, the electronic device transmits the user's voice input to a server that maintains and trains the voice recognition model database.

Abstract: An apparatus includes an echo canceller having an audio signal input and an audio signal output and dynamic pre-conditioning logic. The dynamic pre-conditioning logic is operatively coupled to the echo canceller audio signal output as a feedback signal and has a dynamic pre-conditioning logic output operatively coupled to the echo canceller audio signal input. The dynamic pre-conditioning logic is also operative to receive an audio signal input from at least one microphone. The dynamic pre-conditioning logic is operative to analyze the feedback signal to obtain at least one characteristic, and pre-condition the audio signal input, based on the at least one characteristic of the feedback signal, and provide a pre-conditioned audio signal at the echo canceller audio signal input. The echo canceller audio signal output is then provided to a noise suppressor for the send path of a full duplex communication channel.

Abstract: A method and apparatus for adapting acoustic processing in a communication device, and capturing at least one acoustic signal using acoustic hardware of the communication device, characterizing an acoustic environment external to the communication device using the at least one captured acoustic signal, adapting acoustic processing within the communication device based on the characterized acoustic environment.

Abstract: An electronic device includes a microphone that receives an audio signal that includes a spoken trigger phrase, and a processor that is electrically coupled to the microphone. The processor measures characteristics of the audio signal, and determines, based on the measured characteristics, whether the spoken trigger phrase is acceptable for trigger phrase model training. If the spoken trigger phrase is determined not to be acceptable for trigger phrase model training, the processor rejects the trigger phrase for trigger phrase model training.

Abstract: An electronic device includes a microphone that receives an audio signal, and a processor that is electrically coupled to the microphone. The processor detects a trigger phrase in the received audio signal and measure characteristics of the detected trigger phrase. Based on the measured characteristics of the detected trigger phrase, the processor determines whether the detected trigger phrase is valid.

Abstract: An electronic apparatus is provided that has a rear-side and a front-side, a first microphone that generates a first signal, and a second microphone that generates a second signal. An automated balance controller generates a balancing signal based on a proximity sensor signal. A processor processes the first and second signals to generate at least one beamformed audio signal, where an audio level difference between a front-side gain and a rear-side gain of the beamformed audio signal is controlled during processing based on the balancing signal.

Abstract: A method includes detecting a surface in proximity to a mobile device using sensor data and determining an acoustic reflectivity or acoustic absorptivity of the surface using the sensor data. The method may further compensate for the acoustic reflectivity or acoustic absorptivity by controlling a configurable group of microphones of the mobile device. Compensating for the surface acoustic reflectivity or acoustic absorptivity may include beamforming the outputs of the configurable group of microphones to obtain one of an omnidirectional beamform pattern or a directional beamform pattern. An apparatus that performs the method include a configurable group of microphones, a signal conditioner, and a surface compensator. The surface compensator is operative to detect a surface in proximity to the apparatus and determine a surface acoustic reflectivity or acoustic absorptivity.

Abstract: A disclosed method includes monitoring an audio signal energy level while having a plurality of signal processing components deactivated and activating at least one signal processing component in response to a detected change in the audio signal energy level. The method may include activating and running a voice activity detector on the audio signal in response to the detected change where the voice activity detector is the at least one signal processing component. The method may further include activating and running the noise suppressor only if a noise estimator determines that noise suppression is required. The method may activate and runs a noise type classifier to determine the noise type based on information received from the noise estimator and may select a noise suppressor algorithm, from a group of available noise suppressor algorithms, where the selected noise suppressor algorithm is the most power consumption efficient.

Abstract: A method includes obtaining a speech sample from a pre-processing front-end of a first device, identifying at least one condition, and selecting a voice recognition speech model from a database of speech models, the selected voice recognition speech model trained under the at least one condition. The method may include performing voice recognition on the speech sample using the selected speech model. A device includes a microphone signal pre-processing front end and operating-environment logic, operatively coupled to the pre-processing front end. The operating-environment logic is operative to identify at least one condition. A voice recognition configuration selector is operatively coupled to the operating-environment logic, and is operative to receive information related to the at least one condition from the operating-environment logic and to provide voice recognition logic with an identifier for a voice recognition speech model trained under the at least one condition.

Abstract: A method and apparatus for voice recognition performed in a voice recognition block comprising a plurality of voice recognition stages. The method includes receiving a first plurality of voice inputs, corresponding to a first phrase, into a first voice recognition stage of the plurality of voice recognition stages, wherein multiple ones of the voice recognition stages includes a plurality of voice recognition modules and multiples ones of the voice recognition stages perform a different type of voice recognition processing, wherein the first voice recognition stage processes the first plurality of voice inputs to generate a first plurality of outputs for receipt by a subsequent voice recognition stage. The method further includes, receiving by each subsequent voice recognition stage a plurality of outputs from a preceding voice recognition stage, wherein a plurality of final outputs is generated by a final voice recognition stage from which to approximate the first phrase.