Abstract:
An apparatus (300) includes an echo canceller (13) having an audio signal input and an audio signal output and dynamic pre-conditioning logic (200). The dynamic pre-conditioning logic (200) is operatively coupled to the echo canceller (130) audio signal output as a feedback signal (107) and has a dynamic pre-conditioning logic (200) output operatively coupled to the echo canceller (130) audio signal input. The dynamic pre-conditioning logic (200) is also operative to receive an audio signal input from at least one microphone (210). The dynamic pre-conditioning logic (200) is operative to analyze the feedback signal (107) to obtain at least one characteristic, and pre-condition the audio signal input, based on the at least one characteristic of the feedback signal, and provide a pre-conditioned audio signal at the echo canceller (130) audio signal input. The echo canceller (130) audio signal output is then provided to a noise suppressor (140) for the send path of a full duplex communication channel.
Abstract:
An electronic device includes a microphone (108) that receives an audio signal, and a processor that is electrically coupled to the microphone (108). The processor (204, 300) detects a trigger phrase in the received audio signal and measure characteristics of the detected trigger phrase. Based on the measured characteristics of the detected trigger phrase, the processor (204,300) determines whether the detected trigger phrase is valid.
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:
An electronic device (102) digitally combines a single voice input with each of a series of noise samples. Each noise sample is taken from a different audio environment (e.g., street noise, babble, interior car noise). The voice input / noise sample combinations are used to train a voice recognition model database (308) without the user (104) having to repeat the voice input in each of the different environments. In one variation, the electronic device (102) transmits the user's voice input to a server (301) that maintains and trains the voice recognition model database (308).
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.