Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: An electronic device measures noise variability of background noise present in a sampled audio signal, and determines whether the measured noise variability is higher than a high threshold value or lower than a low threshold value. If the noise variability is determined to be higher than the high threshold value, the device categorizes the background noise as having a high degree of variability. If the noise variability is determined to be lower than the low threshold value, the device categorizes the background noise as having a low degree of variability. The high and low threshold values are between a high boundary point and a low boundary point. The high boundary point is based on an analysis of files including noises that exhibit a high degree of variability, and the low boundary point is based on an analysis of files including noises that exhibit a low degree of variability.

Abstract: A portable electronic communication device includes a user input receiver, one or more user outputs, and a processor programmed to receive user input from the user input receiver and to determine based on the user input whether the user desires the device to enter a private mode. The device alters communications from the device via the one or more user outputs while in the private mode, and enters the private mode if the user input indicates that the user desires the device to enter the private mode. While in the private mode, the device may alter the manner in which it communicates to the user.

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 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 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 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: Systems and methods for voice recognition determine energy levels for speech and noise and generate adaptive thresholds based on the determined energy levels. The adaptive thresholds are applied to determine the presence of speech and to generate noise-dependent triggers for indicating the presence of speech during high-noise conditions. In an embodiment, the signal energy is averaged in the presence of speech and in the presence of background noise. Audio energy calculations may be made by averaging via a sliding window or via a memory filter.

Abstract: Apparatuses, methods, and program products are disclosed for capturing video. In one method, video is captured using a video capturing device. Moreover, capturing the video may include setting a focus of the lens to a first focus plane distance having a first predetermined focus plane distance range. Further, capturing the video may include determining an estimate of a second focus plane distance. Capturing the video may also include determining whether the estimate of the second focus plane distance is outside of the first predetermined focus plane distance range. In addition, capturing the video may include adjusting the focus of the lens of the video capturing device in response to the estimate of the second focus plane distance being outside of the first predetermined focus plane distance range.

Abstract: Systems and methods for controlling a portable electronic communication device use device operational context to provide user trigger or command input. When user input is received from a user of the device, a set of user input options is selected based on an operational context of the device, including an identification of at least one running application. Each user input option is associated with a device action, and the received user input is mapped to a matching user input option within the selected set of user input options. The device action associated with the matching user input option is then executed.

Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.

Abstract: A portable electronic communication device includes a user input receiver, one or more user outputs, and a processor programmed to receive user input from the user input receiver and to determine based on the user input whether the user desires the device to enter a private mode. The device alters communications from the device via the one or more user outputs while in the private mode, and enters the private mode if the user input indicates that the user desires the device to enter the private mode. While in the private mode, the device may alter the manner in which it communicates to the user.

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: 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 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: A method on a mobile device for voice recognition training is described. A voice training mode is entered. A voice training sample for a user of the mobile device is recorded. The voice training mode is interrupted to enter a noise indicator mode based on a sample background noise level for the voice training sample and a sample background noise type for the voice training sample. The voice training mode is returned to from the noise indicator mode when the user provides a continuation input that indicates a current background noise level meets an indicator threshold value.