Methods and systems are described herein for improving audio for hearing impaired content consumers. An example method may comprise determining a content asset. Closed caption data associated with the content asset may be determined. At least a portion of the closed caption data may be determined based on a user setting associated with a hearing impairment. Compensating audio comprising a frequency translation associated with at least the portion of the closed caption data may be generated. The content asset may be caused to be output with audio content comprising the compensating audio and the original audio.

An enunciation system (ES) enables users to gain acquaintance, understanding, and mastery of the relationship between letters and sounds in the context of an alphabetic writing system. The ES enables the user to experience the action of sounding out a word, before their own phonics knowledge enables them to sound out the word independently; its continuous, unbroken speech output or input avoids the common confusions that ensue from analyzing words by breaking them up into discrete sounds; its user-controlled pacing allows the user to slow down enunciation at specific points of difficulty within the word; its real-time touch control allows the written word to be “played” like a musical instrument, with expressive and aesthetic possibilities; and its highlighting of the letter cluster that is responsible for the recognized phoneme enunciated by the user as it occurs allows the user to more easily associated the letters with the sounds.

An enunciation system (ES) enables users to gain acquaintance, understanding, and mastery of the relationship between letters and sounds in the context of an alphabetic writing system. The ES enables the user to experience the action of sounding out a word, before their own phonics knowledge enables them to sound out the word independently; its continuous, unbroken speech output or input avoids the common confusions that ensue from analyzing words by breaking them up into discrete sounds; its user-controlled pacing allows the user to slow down enunciation at specific points of difficulty within the word; its real-time touch control allows the written word to be “played” like a musical instrument, with expressive and aesthetic possibilities; and its highlighting of the letter cluster that is responsible for the recognized phoneme enunciated by the user as it occurs allows the user to more easily associated the letters with the sounds.

Provided is a haptic device including a medium for receiving a digital sound signal from a portable terminal, a digital-to-analog converter (DAC) for receiving the digital sound signal from the medium and converting the digital sound signal into an analog signal, a sound outputter for receiving the analog signal and outputting sound, and a haptic actuator driven by receiving the analog signal.

Provided is a haptic device including a medium for receiving a digital sound signal from a portable terminal, a digital-to-analog converter (DAC) for receiving the digital sound signal from the medium and converting the digital sound signal into an analog signal, a sound outputter for receiving the analog signal and outputting sound, and a haptic actuator driven by receiving the analog signal.

A system includes a first microphone that captures audio, a communication module communicatively coupled to the first microphone, a logic circuit communicatively coupled to the first microphone and communication module, a speaker operatively coupled to the logic circuit, and an interaction element. The interaction element and logic circuit are configured to initiate control of audio content for output from the speaker in response to at least one voice command detected in captured audio. Other embodiments are disclosed.

A system includes a first microphone that captures audio, a communication module communicatively coupled to the first microphone, a logic circuit communicatively coupled to the first microphone and communication module, a speaker operatively coupled to the logic circuit, and an interaction element. The interaction element and logic circuit are configured to initiate control of audio content for output from the speaker in response to at least one voice command detected in captured audio. Other embodiments are disclosed.

Devices for preventing unintended conversation from being recorded by a voice activated assistant device/application (VAD) are disclosed. The device is contoured to fit over a functional surface of a VAD that typically includes a plurality of microphones and control buttons. The device covers the microphones and uses its own microphones to monitor for an authorization input signal. In an embodiment, the devices uses speakers aligned with and opposing each VAD microphone. The device emits interfering audible signals during this mode of operation. Once the device senses an authorization input, the device decouples its speakers from the interfering audible signal and instead allows the device microphones to pass through to the VAD. During this mode, the VAD is in normal operation.

Devices for preventing unintended conversation from being recorded by a voice activated assistant device/application (VAD) are disclosed. The device is contoured to fit over a functional surface of a VAD that typically includes a plurality of microphones and control buttons. The device covers the microphones and uses its own microphones to monitor for an authorization input signal. In an embodiment, the devices uses speakers aligned with and opposing each VAD microphone. The device emits interfering audible signals during this mode of operation. Once the device senses an authorization input, the device decouples its speakers from the interfering audible signal and instead allows the device microphones to pass through to the VAD. During this mode, the VAD is in normal operation.

A method and apparatus for predicting a mouth-shape feature, and an electronic device are provided. A specific implementation of the method comprises: recognizing a phonetic posterior gram (PPG) of a phonetic feature; and performing a prediction on the PPG by using a neural network model, to predict a mouth-shape feature of the phonetic feature, the neural network model being obtained by training with training samples and an input thereof including a PPG and an output thereof including a mouth-shape feature, and the training samples including a PPG training sample and a mouth-shape feature training sample.