Abstract: An audio system encodes and decodes audio captured by a microphone array system in the presence of wind noise. The encoder encodes the audio signal in a way that includes beamformed audio signal and a “hidden” representation of a non-beamformed audio signal. The hidden signal is produced by modulating the low frequency signal to a high frequency above the audible range. A decoder can then either output the beamformed audio signal or can use the hidden signal to generate a reduced wind noise audio signal that includes the non-beamformed audio in the low frequency range.

Abstract: A camera system includes a first microphone, a second microphone, and a microphone controller. The first microphone and the second microphone are configured to capture audio over a time interval to produce a first captured audio signal and a second captured audio signal, respectively. The second captured audio signal is dampened relative to the first captured audio signal by a dampening factor. The microphone controller is configured to store the first captured audio signal in response to a determination that the first captured audio signal does not clip. In response to a determination that the first captured audio signal clips, the microphone controller is configured to identify a gain between the first captured audio signal and the second captured audio signal representative of the dampening factor, amplify the second captured audio signal based on the identified gain, and store the amplified second captured audio signal.

Abstract: A voice activity detector (VAD) combines the use of an acoustic VAD and a vibration sensor VAD as appropriate to the conditions a host device is operated. The VAD includes a first detector receiving a first signal and a second detector receiving a second signal. The VAD includes a first VAD component coupled to the first and second detectors. The first VAD component determines that the first signal corresponds to voiced speech when energy resulting from at least one operation on the first signal exceeds a first threshold. The VAD includes a second VAD component coupled to the second detector. The second VAD component determines that the second signal corresponds to voiced speech when a ratio of a second parameter corresponding to the second signal and a first parameter corresponding to the first signal exceeds a second threshold.

Abstract: A spherical content capture system captures spherical video and audio content. In one embodiment, captured metadata or video/audio processing is used to identify content relevant to a particular user based on time and location information. The platform can then generate an output video from one or more shared spherical content files relevant to the user. The output video may include a non-spherical reduced field of view such as those commonly associated with conventional camera systems. Particularly, relevant sub-frames having a reduced field of view may be extracted from each frame of spherical video to generate an output video that tracks a particular individual or object of interest. For each sub-frame, a corresponding portion of an audio track is generated that includes a directional audio signal having a directionality based on the selected sub-frame.

Abstract: A wireless conference call telephone system uses body-worn wired or wireless audio endpoints comprising microphones and, optionally, speakers. These audio-endpoints, which include headsets, pendants, and clip-on microphones to name a few, are used to capture the user's voice and the resulting data may be used to remove echo and environmental acoustic noise. Each audio-endpoint transmits its audio to the telephony gateway, where noise and echo suppression can take place if not already performed on the audio-endpoint, and where each audio-endpoint's output can be labeled, integrated with the output of other audio-endpoints, and transmitted over one or more telephony channels of a telephone network. The noise and echo suppression can also be done on the audio-endpoint. The labeling of each user's output can be used by the outside caller's phone to spatially locate each user in space, increasing intelligibility.

Abstract: A wireless conference call telephone system uses body-worn wired or wireless audio endpoints comprising microphone arrays and, optionally, speakers. These audio-endpoints, which include headsets, pendants, and clip-on microphones to name a few, are used to capture the user's voice and the resulting data may be used to remove echo and environmental acoustic noise. Each audio-endpoint transmits its audio to the telephony gateway, where noise and echo suppression can take place if not already performed on the audio-endpoint, and where each audio-endpoint's output can be labeled, integrated with the output of other audio-endpoints, and transmitted over one or more telephony channels of a telephone network. The noise and echo suppression can also be done on the audio-endpoint. The labeling of each user's output can be used by the outside caller's phone to spatially locate each user in space, increasing intelligibility.

Abstract: A voice activity detector (VAD) combines the use of an acoustic VAD and a vibration sensor VAD as appropriate to the conditions a host device is operated. The VAD includes a first detector receiving a first signal and a second detector receiving a second signal. The VAD includes a first VAD component coupled to the first and second detectors. The first VAD component determines that the first signal corresponds to voiced speech when energy resulting from at least one operation on the first signal exceeds a first threshold. The VAD includes a second VAD component coupled to the second detector. The second VAD component determines that the second signal corresponds to voiced speech when a ratio of a second parameter corresponding to the second signal and a first parameter corresponding to the first signal exceeds a second threshold.

Abstract: Acoustic Voice Activity Detection (AVAD) methods and systems are described. The AVAD methods and systems, including corresponding algorithms or programs, use microphones to generate virtual directional microphones which have very similar noise responses and very dissimilar speech responses. The ratio of the energies of the virtual microphones is then calculated over a given window size and the ratio can then be used with a variety of methods to generate a VAD signal. The virtual microphones can be constructed using either an adaptive or a fixed filter.

Abstract: Acoustic Voice Activity Detection (AVAD) methods and systems are described. The AVAD methods and systems, including corresponding algorithms or programs, use microphones to generate virtual directional microphones which have very similar noise responses and very dissimilar speech responses. The ratio of the energies of the virtual microphones is then calculated over a given window size and the ratio can then be used with a variety of methods to generate a VAD signal. The virtual microphones can be constructed using either an adaptive or a fixed filter.

Abstract: A voice activity detector (VAD) combines the use of an acoustic VAD and a vibration sensor VAD as appropriate to the conditions a host device is operated. The VAD includes a first detector receiving a first signal and a second detector receiving a second signal. The VAD includes a first VAD component coupled to the first and second detectors. The first VAD component determines that the first signal corresponds to voiced speech when energy resulting from at least one operation on the first signal exceeds a first threshold. The VAD includes a second VAD component coupled to the second detector. The second VAD component determines that the second signal corresponds to voiced speech when a ratio of a second parameter corresponding to the second signal and a first parameter corresponding to the first signal exceeds a second threshold.

Abstract: Acoustic Voice Activity Detection (AVAD) methods and systems are described. The AVAD methods and systems, including corresponding algorithms or programs, use microphones to generate virtual directional microphones which have very similar noise responses and very dissimilar speech responses. The ratio of the energies of the virtual microphones is then calculated over a given window size and the ratio can then be used with a variety of methods to generate a VAD signal. The virtual microphones can be constructed using either an adaptive or a fixed filter.

Abstract: Acoustic Voice Activity Detection (AVAD) methods and systems are described. The AVAD methods and systems, including corresponding algorithms or programs, use microphones to generate virtual directional microphones which have very similar noise responses and very dissimilar speech responses. The ratio of the energies of the virtual microphones is then calculated over a given window size and the ratio can then be used with a variety of methods to generate a VAD signal. The virtual microphones can be constructed using either an adaptive or a fixed filter.

Abstract: A wireless conference call telephone system uses body-worn wired or wireless audio endpoints comprising microphone arrays and, optionally, speakers. These audio-endpoints, which include headsets, pendants, and clip-on microphones to name a few, are used to capture the user's voice and the resulting data may be used to remove echo and environmental acoustic noise. Each audio-endpoint transmits its audio to the telephony gateway, where noise and echo suppression can take place if not already performed on the audio-endpoint, and where each audio-endpoint's output can be labeled, integrated with the output of other audio-endpoints, and transmitted over one or more telephony channels of a telephone network. The noise and echo suppression can also be done on the audio-endpoint. The labeling of each user's output can be used by the outside caller's phone to spatially locate each user in space, increasing intelligibility.

Abstract: Various embodiments relate to signal processing and, more particularly, to processing of received speech signals to preserve and enhance speech intelligibility. In one embodiment, a communications apparatus includes a receiving path over which received speech signals traverse in an audio stream, and an dynamic audio enhancement device disposed in the receiving path. The dynamic audio enhancement (“DAE”) device is configured to modify an amount of volume and an amount of equalization of the audio stream. The DAE device can include a noise level estimator (“NLE”) configured to generate a signal representing a noise level estimate. The noise level estimator can include a non-stationary noise detector and a stationary noise detector. The noise level estimator can be configured to generate the signal representing a first noise level estimate based on detection of the non-stationary noise or a second noise level estimate based on detection of the stationary noise.

Abstract: Techniques for acoustic voice activity detection (AVAD) is described, including detecting a signal associated with a subband from a microphone, performing an operation on data associated with the signal, the operation generating a value associated with the subband, and determining whether the value distinguishes the signal from noise by using the value to determine a signal-to-noise ratio and comparing the value to a threshold.

Abstract: A wireless conference call telephone system uses body-worn wired or wireless audio endpoints comprising microphones and, optionally, speakers. These audio-endpoints, which include headsets, pendants, and clip-on microphones to name a few, are used to capture the user's voice and the resulting data may be used to remove echo and environmental acoustic noise. Each audio-endpoint transmits its audio to the telephony gateway, where noise and echo suppression can take place if not already performed on the audio-endpoint, and where each audio-endpoint's output can be labeled, integrated with the output of other audio-endpoints, and transmitted over one or more telephony channels of a telephone network. The noise and echo suppression can also be done on the audio-endpoint. The labeling of each user's output can be used by the outside caller's phone to spatially locate each user in space, increasing intelligibility.

Abstract: A voice activity detector (VAD) combines the use of an acoustic VAD and a vibration sensor VAD as appropriate to the conditions a host device is operated. The VAD includes a first detector receiving a first signal and a second detector receiving a second signal. The VAD includes a first VAD component coupled to the first and second detectors. The first VAD component determines that the first signal corresponds to voiced speech when energy resulting from at least one operation on the first signal exceeds a first threshold. The VAD includes a second VAD component coupled to the second detector. The second VAD component determines that the second signal corresponds to voiced speech when a ratio of a second parameter corresponding to the second signal and a first parameter corresponding to the first signal exceeds a second threshold.

Abstract: Acoustic Voice Activity Detection (AVAD) methods and systems are described. The AVAD methods and systems, including corresponding algorithms or programs, use microphones to generate virtual directional microphones which have very similar noise responses and very dissimilar speech responses. The ratio of the energies of the virtual microphones is then calculated over a given window size and the ratio can then be used with a variety of methods to generate a VAD signal. The virtual microphones can be constructed using either an adaptive or a fixed filter.

Abstract: Acoustic Voice Activity Detection (AVAD) methods and systems are described. The AVAD methods and systems, including corresponding algorithms or programs, use microphones to generate virtual directional microphones which have very similar noise responses and very dissimilar speech responses. The ratio of the energies of the virtual microphones is then calculated over a given window size and the ratio can then be used with a variety of methods to generate a VAD signal. The virtual microphones can be constructed using either an adaptive or a fixed filter.