Abstract: In an audio signal, one or more processing circuits recognize spoken content in a user's own speech signal using speech recognition and natural language understanding. The spoken content describes a listening difficulty of the user. The one or more processing circuits generate, based on the spoken content, one or more actions for hearing devices and feedback for the user. The one or more actions attempt to resolve the listening difficulty. Additionally, the one or more processing circuits convert the user feedback to verbal feedback using speech synthesis and transmit the one or more actions and the verbal feedback to the hearing devices via a body-worn device. The hearing devices are configured to perform the one or more actions and play back the verbal feedback to the user.

Abstract: A computing system includes a memory and at least one processor. The memory is configured to store motion data indicative of motion of a hearing instrument. The at least one processor is configured to determine a type of activity performed by a user of the hearing instrument and output data indicating the type of activity performed by the user.

Abstract: In an audio signal, one or more processing circuits recognize spoken content in a user's own speech signal using speech recognition and natural language understanding. The spoken content describes a listening difficulty of the user. The one or more processing circuits generate, based on the spoken content, one or more actions for hearing devices and feedback for the user. The one or more actions attempt to resolve the listening difficulty. Additionally, the one or more processing circuits convert the user feedback to verbal feedback using speech synthesis and transmit the one or more actions and the verbal feedback to the hearing devices via a body-worn device. The hearing devices are configured to perform the one or more actions and play back the verbal feedback to the user.

Abstract: In an audio signal, one or more processing circuits recognize spoken content in a user's own speech signal using speech recognition and natural language understanding. The spoken content describes a listening difficulty of the user. The one or more processing circuits generate, based on the spoken content, one or more actions for hearing devices and feedback for the user. The one or more actions attempt to resolve the listening difficulty. Additionally, the one or more processing circuits convert the user feedback to verbal feedback using speech synthesis and transmit the one or more actions and the verbal feedback to the hearing devices via a body-worn device. The hearing devices are configured to perform the one or more actions and play back the verbal feedback to the user.

Abstract: A maximum-kurtosis, distortionless response (MKDR) technique and an extension, the maximum-kurtosis, Wiener estimate (MKWE) technique, are provided. In one form, blind estimates of the speech source's channel response are made from the microphone data and MVDR is applied. The source direction is estimated by finding weights that maximize output kurtosis, or the fourth central statistical moment, in the frequency domain. The MKWE approach approximates the Wiener filter by using MKDR-output noise power estimates to compute a Wiener post-filter. These approaches can be extended to block-adaptive versions if the speech source is not quickly moving in space.

Abstract: A maximum-kurtosis, distortionless response (MKDR) technique and an extension, the maximum-kurtosis, Wiener estimate (MKWE) technique, are provided. In one form, blind estimates of the speech source's channel response are made from the microphone data and MVDR is applied. The source direction is estimated by finding weights that maximize output kurtosis, or the fourth central statistical moment, in the frequency domain. The MKWE approach approximates the Wiener filter by using MKDR-output noise power estimates to compute a Wiener post-filter. These approaches can be extended to block-adaptive versions if the speech source is not quickly moving in space.