Apple Inc.

Other

Creative Technology Corporation

Arvindh Krishnaswamy

Sean Anthony Ramprashad

Joseph M Williams

Aram M Lindahl

Juha O Merimaa

Harvey D Thornburg

Sarmad Aziz Malik

Xiaoyuan Tu

Justin N Wood

Roberto Garcia

Anil K Kandangath

David T Yeh

Kapil Krishnamurthy

Yuchao Song

Jean-Marc Jot

Michael M Goodwin

Jean Laroche

Andrew P Bright

Juha Merimaa

Charles Pascal Clark

An electronic device displays a messaging interface that allows a participant in a message conversation to capture, send, and/or play media content. The media content includes images, video, and/or audio. The media content is captured, sent, and/or played based on the electronic device detecting one or more conditions.

Message user interfaces for capture and transmittal of media and location content

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.

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.

Multi-microphone speech recognition systems and related techniques

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.

System and method for echo control using adaptive polynomial filters in a sub-band domain

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.

Systems and methods for adjusting automatic gain control

Apparatus for linear and nonlinear acoustic echo control includes loudspeaker, first, second, and third microphone, beamformer, and first echo canceller. The loudspeaker outputs a loudspeaker signal that includes reference signal. The first microphone and the second microphone are collocated with the loudspeaker, receive at least one of: a near-end speaker signal from a near-end speaker and the loudspeaker signal, and generate first and second microphone uplink signals, respectively. The third microphone receives the near-end speaker signal and generates a third microphone uplink signal. The beamformer receives the first and second microphone uplink signals, directs a beam towards the loudspeaker and drives a null towards the near-end speaker, and generates a beamformer output. The first echo canceler receives the third microphone uplink signal and the beamformer output, and cancels echoes in the third microphone uplink signal based on the beamformer output to generate an echo cancelled signal. Other embodiments are described.

Apparatus and method for linear and nonlinear acoustic echo control using additional microphones collocated with a loudspeaker

Method of improving audio signal in the spectral domain starts by receiving audio signal that includes signals from sources including speech source and music source. Audio signal is tuned for output by sound output device. Portions of audio signal are analyzed in a spectral domain to determine whether adjustments are required. Analyzing portions of audio signal includes determining whether anomaly is present in frequency band of audio signal in spectral domain by using at least one metric. Metrics include band energy ratios, spectral centroid, spectral tilt, spectral flux, spectral variance, absolute thresholds, and relative thresholds. Audio signal is adjusted to improve audio signal in spectral domain when audio signal is determined to require adjustments. Adjusting audio signal includes adjusting values of the metric in frequency band that is determined to include anomaly to correspond to clustering of metric values for audio signal in spectral domain. Other embodiments are also described.

Apparatus and method for improving an audio signal in the spectral domain

Systems and methods for speech recognition system having a speech processor that is trained to recognize speech by considering (1) a raw microphone signal that includes an echo signal and (2) different types of echo information signals from an echo cancellation system (and optionally different types of ambient noise suppression signals from a noise suppressor). The different types of echo information signals may include those used for echo cancelation and those having echo information. The speech recognition system may convert the raw microphone signal and different types of echo information signals (and optional noise suppression signals) into spectral features in the form of a vector, and a concatenator to combine the feature vectors into a total vector (for a period of time) that is used to train the speech processor, and during use of the speech processor to recognize speech.

Robust speech recognition in the presence of echo and noise using multiple signals for discrimination

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.

System and method for dynamically adapting playback device volume on an electronic device

Apparatus for optimizing beamformers for echo control comprises microphones to receive acoustic signals, echo cancellers (ECs) respectively coupled to the microphones to adaptively cancel echo in the acoustic signals and to generate EC-acoustic signals, and a first fixed beamformer coupled to the ECs to receive the EC-acoustic signals. The null of the first beamformer is steered in a direction of a first environmental noise source that is determined offline by exciting the ECs with normal speech signals and audio playback signals to cause the ECs to generate test EC-acoustic signals, and selecting the first environmental noise source based on loudness weighted centroids of noise in the test EC-acoustic signals. Apparatus may also include a residual echo suppressor coupled to the first fixed beamformer to perform echo suppression on output of the first fixed beamformer and to generate clean signal. Other embodiments are also described.

System and method of optimizing a beamformer for echo control

A multi-band audio compressor that may provide not only better and brighter sound, but also speaker protection. The multi-band audio compressor breaks an input audio signal into different frequency bands. For each band signal, a volume re-mapper translates a user preference volume level to a converted volume level based on a programmable volume curve for the band signal. For each frequency band, the band signal is processed by a gain stage and a compressor. Each gain stage applies a signal gain to the band signal based on the converted volume level. Each compressor compresses the output of the gain stage. After compression, the different frequency band signals are re-combined and the combined audio signal may then be passed to a power amplifier that is driving a speaker. Other embodiments are also described and claimed.

Intelligent dynamics processing

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.

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San Jose, CA, United States of America

Arvindh Krishnaswamy