Abstract:
A method and apparatus for adapting acoustic processing in a communication device (102), and capturing (302) at least one acoustic signal using acoustic hardware (218, 224) of the communication device (102), characterizing (304) an acoustic environment external to the communication device (102) using the at least one captured acoustic signal, adapting (306) acoustic processing within the communication device (102) based on the characterized acoustic environment.
Abstract:
An apparatus (100) includes a group of microphones (110) and a surface compensator (200) that is operatively coupled to switch logic (120) and to a signal conditioner (160) that provides a control channel (125) to voice recognition logic (101). The surface compensator (200) may detect surfaces in proximity to the apparatus (100) as well as the surface's acoustic reflectivity or acoustic absorptivity and may accordingly configure the group of microphones (110) including selecting appropriate signal conditioning and beamforming based on the surface acoustic reflectivity or acoustic absorptivity and the orientation of the apparatus (100). Voice recognition (101) performance is thus improved when microphones are impeded or occluded by proximate surfaces. A group of sensors of the apparatus (100) is used by the surface compensator (200) to detect surfaces and surface type, and to determine apparatus (100) orientation and motion.
Abstract:
A disclosed method includes monitoring an audio signal energy level while having a plurality of signal processing components deactivated and activating at least one signal processing component in response to a detected change in the audio signal energy level. The method may include activating and running a voice activity detector (150) on the audio signal in response to the detected change where the voice activity detector (150) is the at least one signal processing component. The method may further include activating and running the noise suppressor (190) only if a noise estimator (160) determines that noise suppression is required. The method may activate and runs a noise type classifier (170) to determine the noise type based on information received from the noise estimator (160) and may select a noise suppressor algorithm, from a group of available noise suppressor algorithms (109), where the selected noise suppressor algorithm is the most power consumption efficient.