Methods and devices to deliver a tactile speech analog to a person's skin providing a silent, invisible, hands-free, eyes-free, and ears-free way to receive and directly comprehend electronic communications. Embodiments include an alternative to hearing aids that will enable people with hearing loss to better understand speech. A device, worn like watch or bracelet, supplements a person's remaining hearing to help identify and disambiguate those sounds he or she can not hear properly. Embodiments for hearing aids and hearing prosthetics are also described.

Disclosed are a display apparatus, a voice acquiring apparatus and a voice recognition method thereof, the display apparatus including: a display unit which displays an image; a communication unit which communicates with a plurality of external apparatuses; and a controller which includes a voice recognition engine to recognize a user's voice, receives a voice signal from a voice acquiring unit, and controls the communication unit to receive candidate instruction words from at least one of the plurality of external apparatuses to recognize the received voice signal.

Disclosed are a display apparatus, a voice acquiring apparatus and a voice recognition method thereof, the display apparatus including: a display unit which displays an image; a communication unit which communicates with a plurality of external apparatuses; and a controller which includes a voice recognition engine to recognize a user's voice, receives a voice signal from a voice acquiring unit, and controls the communication unit to receive candidate instruction words from at least one of the plurality of external apparatuses to recognize the received voice signal.

A lip language recognition method, applied to a mobile terminal having a sound mode and a silent mode, includes: training a deep neural network in the sound mode; collecting a user's lip images in the silent mode; and identifying content corresponding to the user's lip images with the deep neural network trained in the sound mode. The method further includes: switching from the sound mode to the silent mode when a privacy need of the user arises.

Disclosed is a method for controlling a cordless telephone device for use in a system that allows remote control of a home electric appliance. The method includes a first generation step of causing a first generation unit in a handset to encode audio input via a sound receiving unit in the handset to generate a first stream, and a first transmission step of transmitting the first stream to a base unit. The first generation step includes causing the first generation unit to generate instruction bit information and a first instruction stream when a first trigger indicating a request to start the remote control is given to the first generation unit. The first transmission step includes transmitting the instruction bit information and the first instruction stream to the base unit through a multiplexing scheme that is common to transmission of a first stream generated when the first trigger is not given.

In various embodiments, a computer-implemented method of training a neural network for creating an output signal of different modality from an input signal is described. In embodiments, the first modality may be a sound signal or a visual image and where the output signal would be a visual image or a sound signal, respectively. In embodiments a model is trained using a first pair of visual and audio networks to train a set of codebooks using known visual signals and the audio signals and using a second pair of visual and audio networks to further train the set of codebooks using the augmented visual signals and the augmented audio signals. Further, the first and the second visual networks are equally weighted and where the first and the second audio networks are equally weighted. In aspects of the present disclosure, the set of codebooks comprise a visual codebook, an audio codebook and a correlation codebook. These codebooks are then used to create an visual image from a sound signal and/or a sound signal from a visual image.

A semantic recognition method and a semantic recognition device are provided. A spectrogram of a speech signal is generated. At least one keyword of the spectrogram is detected by inputting the spectrogram into a neural network model. A semantic category to which each of the at least one keyword belongs is distinguished. A semantic intention of the speech signal is determined according to the at least one keyword and the semantic category of the at least one keyword.

A semantic recognition method and a semantic recognition device are provided. A spectrogram of a speech signal is generated. At least one keyword of the spectrogram is detected by inputting the spectrogram into a neural network model. A semantic category to which each of the at least one keyword belongs is distinguished. A semantic intention of the speech signal is determined according to the at least one keyword and the semantic category of the at least one keyword.

Disclosed are a display apparatus, a voice acquiring apparatus and a voice recognition method thereof, the display apparatus including: a display unit which displays an image; a communication unit which communicates with a plurality of external apparatuses; and a controller which includes a voice recognition engine to recognize a user’s voice, receives a voice signal from a voice acquiring unit, and controls the communication unit to receive candidate instruction words from at least one of the plurality of external apparatuses to recognize the received voice signal.

Disclosed are a display apparatus, a voice acquiring apparatus and a voice recognition method thereof, the display apparatus including: a display unit which displays an image; a communication unit which communicates with a plurality of external apparatuses; and a controller which includes a voice recognition engine to recognize a user’s voice, receives a voice signal from a voice acquiring unit, and controls the communication unit to receive candidate instruction words from at least one of the plurality of external apparatuses to recognize the received voice signal.