Abstract:
Method of dynamically adapting playback volume on electronic device starts with processor receiving first user input and first portion of audio content. First user input signals to device to increase or decrease volume of sound output. Processor determines first loudness metric corresponding to first portion of audio content when first user input is received. First loudness metric is measure of loudness of first portion of audio content being outputted. Processor then stores in memory first loudness metric in association with first user input. Memory stores history of loudness metrics in association with user inputs. Processor then determines second loudness metric that is measure of loudness of second portion of audio content that is received and determines second user input associated with second loudness metric using history. Processor generates control signal to automatically control volume of sound output by device corresponding to second user input. Other embodiments are also described.
Abstract:
A speech recognition system for resolving impaired utterances can have a speech recognition engine configured to receive a plurality of representations of an utterance and concurrently to determine a plurality of highest-likelihood transcription candidates corresponding to each respective representation of the utterance. The recognition system can also have a selector configured to determine a most-likely accurate transcription from among the transcription candidates. As but one example, the plurality of representations of the utterance can be acquired by a microphone array, and beamforming techniques can generate independent streams of the utterance across various look directions using output from the microphone array.
Abstract:
Method of dynamically adapting user volume input range on mobile device having global volume range starts by receiving a volume input selection from a user that is level included in user volume input range. User volume input range is a portion of global volume range. Device's processor then detects ambient noise level surrounding device and adjusts user volume input range from current portion of global volume range to different portion of global volume range based on detected ambient noise level. Volume input selection remains at the same level included in user volume input range after user volume input range is adjusted. Processor may identify sound profile that corresponds to ambient noise level being detected and adjusts user volume input range to a different portion of the global volume range based on identified sound profile. Other embodiments are also described.
Abstract:
Automatic gain control systems disclosed herein can incorporate a confidence metric that can estimate the accuracy of gain adjustments calculated by an automatic gain control module. The confidence metric may be based on a percentage of valid audio samples in a given period of time. Based on the confidence metric, the AGC response may be reduced, delayed, frozen, or otherwise altered from the baseline gain adjustment. Time-averaging process may be used to estimate the input signal power level and determine an appropriate baseline gain adjustment. Additionally, weighting functions can be adjusted to prevent overestimation of the signal power.
Abstract:
An equalizer that linearly interpolates between two equalization states when transitioning from one equalization state to the other equalization state is described. The equalizer includes a transfer function generator and an equalization module. Each equalization state is defined or determined based on a set of parameters. The transfer function generator generates a set of interpolated transfer functions by performing linear interpolation on a first equalization state and a second equalization state based on the set of parameters. The linear interpolation is performed on corresponding Z-domain poles and zeros of the transfer functions of the first and second equalization states. The equalization module applies the set of interpolated transfer functions generated by the transfer function generator to an input audio signal.
Abstract:
Automatic gain control systems disclosed herein can incorporate a confidence metric that can estimate the accuracy of gain adjustments calculated by an automatic gain control module. The confidence metric may be based on a percentage of valid audio samples in a given period of time. Based on the confidence metric, the AGC response may be reduced, delayed, frozen, or otherwise altered from the baseline gain adjustment. Time-averaging process may be used to estimate the input signal power level and determine an appropriate baseline gain adjustment. Additionally, weighting functions can be adjusted to prevent overestimation of the signal power.
Abstract:
An electronic device includes a touch-sensitive surface, a display, and a camera sensor. The device displays a message region for displaying a message conversation and receives a request to add media to the message conversation. Responsive to receiving the request, the device displays a media selection interface concurrently with at least a portion of the message conversation. The media selection interface includes a plurality of affordances for selecting media for addition to the message conversation, the plurality of affordances includes a live preview affordance, at least a subset of the plurality of affordances includes thumbnail representations of media available for adding to the message conversation, and the live preview affordance is associated with a live camera preview. Responsive to detecting selection of the live preview affordance, the device captures a new image based on the live camera preview and selects the new image for addition to the message conversation.
Abstract:
Method for echo control using adaptive polynomial filters in sub-band domain starts with loudspeaker that is configured to be driven by a reference signal outputting a loudspeaker signal. Microphone receives at least one of: a near-end speaker signal, ambient noise signal, or the loudspeaker signal and generates a microphone signal. Adaptive polynomial filters in sub-band domain included in adaptive echo canceller (AEC) are configured to adaptively filter representation of the reference signal in a plurality of channels in a sub-band domain based on a clean signal to generate the echo estimate. Echo suppressor is configured to remove an echo estimate from the microphone signal to generate the clean signal. Other embodiments are described.
Abstract:
A speech recognition system for resolving impaired utterances can have a speech recognition engine configured to receive a plurality of representations of an utterance and concurrently to determine a plurality of highest-likelihood transcription candidates corresponding to each respective representation of the utterance. The recognition system can also have a selector configured to determine a most-likely accurate transcription from among the transcription candidates. As but one example, the plurality of representations of the utterance can be acquired by a microphone array, and beamforming techniques can generate independent streams of the utterance across various look directions using output from the microphone array.
Abstract:
A speech recognition system for resolving impaired utterances can have a speech recognition engine configured to receive a plurality of representations of an utterance and concurrently to determine a plurality of highest-likelihood transcription candidates corresponding to each respective representation of the utterance. The recognition system can also have a selector configured to determine a most-likely accurate transcription from among the transcription candidates. As but one example, the plurality of representations of the utterance can be acquired by a microphone array, and beamforming techniques can generate independent streams of the utterance across various look directions using output from the microphone array.