Abstract: A hearing protection device is disclosed which incorporates integrated audiometric testing, thereby allowing for testing without removal of safety hearing protection. The hearing protection is typically intended to be worn for the duration of a work shift, and allows for self-testing during the shift. Embodiments of the device may utilize a series of partial test sessions, so that each test session is kept brief so as to not interfere unduly with the work schedule. This may encourage frequent testing, hopefully aiding in early detection of potential hearing loss. Additionally, methods of use are disclosed.

Abstract: Embodiments relate generally to an active hearing protection device comprising a communication device operable to provide active hearing protection to a wearer; a set of earmuffs connected to the communication device, wherein each earmuff comprises an indicator mechanism operable to indicate to the communication device when the earmuff is inserted into a user's ear, a processor operable to receive information from the set of earmuffs and the indicator mechanisms of the earmuffs, and operable to automatically power the active hearing protection device on or off based on the information received from the indicator mechanism(s). When it is determined that both earmuffs are inserted into the user's ears, the active hearing protection device is powered on, and when it is determined that at least one of the earmuffs is not inserted into the user's ear(s), the active hearing protection device is powered off.

Abstract: A system and method include sensing sound on the inside of a protective seal of a hearing protection device being worn, and using a sliding window algorithm to calculate the sound to which the ear of the wearer is exposed. The method may also include sensing noise and generating sound to cancel the sensed noise within the ear of the wearer. It may also include sensing ambient sound and regenerating this sound at safe levels inside the hearing protection device in order to aid situational awareness, and it may include receiving signals that are then regenerated as audio inside the hearing protection device for communication or entertainment purposes.

Abstract: A hearing protection device is disclosed which incorporates integrated audiometric testing, thereby allowing for testing without removal of safety hearing protection. The hearing protection is typically intended to be worn for the duration of a work shift, and allows for self-testing during the shift. Embodiments of the device may utilize a series of partial test sessions, so that each test session is kept brief so as to not interfere unduly with the work schedule. This may encourage frequent testing, hopefully aiding in early detection of potential hearing loss. Additionally, methods of use are disclosed.

Abstract: Speech feature vectors (10) are provided and utilized to develop a corresponding estimated speaker dependent speech feature space model (20) (in one embodiment, it is not necessary that this model (20) have defined correlations with the verbal content of the represented speech itself). A model alignment unit (21) then contrasts this model (20) against the contents of a speaker independent speech feature space model (24) to provide alignment indices to a transformation estimation unit (23). In one embodiment, these alignment indices are based, as least in part, upon a measure of the differences between likelihoods of occurrence for the elements that comprise the constituency of these models. The transformation estimation unit (23) utilizes these alignment indices to provide transformation parameters to a model transformation unit (25) that uses such parameters to transform a speaker independent speech recognition model set (26) and yield a resultant speaker adapted speech recognition model set (27).

Abstract: Speech feature vectors (10) are provided and utilized to develop a corresponding estimated speaker dependent speech feature space model (20) (in one embodiment, it is not necessary that this model (20) have defined correlations with the verbal content of the represented speech itself). A model alignment unit (21) then contrasts this model (20) against the contents of a speaker independent speech feature space model (24) to provide alignment indices to a transformation estimation unit (23). In one embodiment, these alignment indices are based, as least in part, upon a measure of the differences between likelihoods of occurrence for the elements that comprise the constituency of these models. The transformation estimation unit (23) utilizes these alignment indices to provide transformation parameters to a model transformation unit (25) that uses such parameters to transform a speaker independent speech recognition model set (26) and yield a resultant speaker adapted speech recognition model set (27).