The present disclosure relates generally to content delivery techniques in audio-visual streaming systems. The techniques include altering video or audio portions of media content based on user input or interaction. The techniques further include altering text or messaging distributed to multiple users based on user input.

One example discloses an apparatus for sound signal detection, comprising: a first wireless device including a first pressure sensor having a first acoustical profile and configured to capture a first set of acoustic energy within a time window; wherein the first wireless device includes a wireless signal input; wherein the first wireless device includes a processing element configured to: receive, through the wireless signal input, a second set of acoustic energy captured by a second pressure sensor, having a second acoustical profile, within a second wireless device and within the time window; apply a signal enhancement technique to the first and second sets of acoustic energy based on the first and second acoustical profiles; search for a predefined sound signal within the enhanced sets of acoustic energy; and initiate a subsequent set of sound signal detection actions if the search finds the sound signal.

One example discloses an apparatus for sound signal detection, comprising: a first wireless device including a first pressure sensor having a first acoustical profile and configured to capture a first set of acoustic energy within a time window; wherein the first wireless device includes a wireless signal input; wherein the first wireless device includes a processing element configured to: receive, through the wireless signal input, a second set of acoustic energy captured by a second pressure sensor, having a second acoustical profile, within a second wireless device and within the time window; apply a signal enhancement technique to the first and second sets of acoustic energy based on the first and second acoustical profiles; search for a predefined sound signal within the enhanced sets of acoustic energy; and initiate a subsequent set of sound signal detection actions if the search finds the sound signal.

An audio signal processing method including obtaining a first audio signal by generating a pattern in association with the first audio signal to be output, outputting the first audio signal, receiving, through an external voice input device while the external voice input device is communicatively connected to the audio signal processing device, a second audio signal including the output first audio signal, detecting the pattern from the second audio signal, and synchronizing the second audio signal with the first audio signal based on the pattern detected from the second audio signal and the pattern included in the first audio signal.

Embodiments of the invention may be used to implement a rate converter that includes: 6 channels in forward (audio) path, each channel having a 24-bit signal path per channel, an End-to-end SNR of 110 dB, all within the 20 Hz to 20 KHz bandwidth. Embodiment may also be used to implement a rate converter having: 2 channels in a reverse path, such as for voice signals, 16-bit signal path per channel, an End-to-end SNR of 93 dB, all within 20 Hz to 20 KHz bandwidth. The rate converter may include sample rates such as 8, 11.025, 12, 16, 22.05, 24, 32 44.1, 48, and 96 KHz. Further, rate converters according to embodiments may include a gated clock in low-power mode to conserve power.

Embodiments of the invention may be used to implement a rate converter that includes: 6 channels in forward (audio) path, each channel having a 24-bit signal path per channel, an End-to-end SNR of 110 dB, all within the 20 Hz to 20 KHz bandwidth. Embodiment may also be used to implement a rate converter having: 2 channels in a reverse path, such as for voice signals, 16-bit signal path per channel, an End-to-end SNR of 93 dB, all within 20 Hz to 20 KHz bandwidth. The rate converter may include sample rates such as 8, 11.025, 12, 16, 22.05, 24, 32 44.1, 48, and 96 KHz. Further, rate converters according to embodiments may include a gated clock in low-power mode to conserve power.

Embodiments of the invention may be used to implement a rate converter that includes: 6 channels in forward (audio) path, each channel having a 24-bit signal path per channel, an End-to-end SNR of 110 dB, all within the 20 Hz to 20 KHz bandwidth. Embodiment may also be used to implement a rate converter having: 2 channels in a reverse path, such as for voice signals, 16-bit signal path per channel, an End-to-end SNR of 93 dB, all within 20 Hz to 20 KHz bandwidth. The rate converter may include sample rates such as 8, 11.025, 12, 16, 22.05, 24, 32 44.1, 48, and 96 KHz. Further, rate converters according to embodiments may include a gated clock in low-power mode to conserve power.

Embodiments of the invention may be used to implement a rate converter that includes: 6 channels in forward (audio) path, each channel having a 24-bit signal path per channel, an End-to-end SNR of 110 dB, all within the 20 Hz to 20 KHz bandwidth. Embodiment may also be used to implement a rate converter having: 2 channels in a reverse path, such as for voice signals, 16-bit signal path per channel, an End-to-end SNR of 93 dB, all within 20 Hz to 20 KHz bandwidth. The rate converter may include sample rates such as 8, 11.025, 12, 16, 22.05, 24, 32 44.1, 48, and 96 KHz. Further, rate converters according to embodiments may include a gated clock in low-power mode to conserve power.

Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face. The trained autoencoder is used to generate an output where the likeness of the face in the destination images is swapped with the likeness of the source face, while preserving expressions of the destination face.

Upon detecting input of an instruction to change a display layout of a document on a display screen, display control of the document on the display screen is performed so that a character output as a voice by a voice output unit at the time of detection is displayed on the display screen.