Qualcomm Incorporated

Dongmei Wang

Erik Visser

Lae-Hoon Kim

Fatemeh Saki

Rogerio Guedes Alves

Taher Shahbazi Mirzahasanloo

Cheng-Yu Hung

Shuhua Zhang

Anne Katrin Konertz

Sharon Kaziunas

Yinyi Guo

In general, techniques are described that enable voice activation for computing devices. A computing device configured to support an audible interface that comprises a memory and one or more processors may be configured to perform the techniques. The memory may store a first audio signal representative of an environment external to a user associated with the computing device and a second audio signal sensed by a microphone coupled to a housing of the computing device. The one or more processors may verify, based on the first audio signal and the second audio signal, that the user activated the audible interface of the computing device, and obtain, based on the verification, additional audio signals representative of one or more audible commands.

Voice activation for computing devices

A wearable device may include a processor configured to detect a self-voice signal, based on one or more transducers. The processor may be configured to separate the self-voice signal from a background signal in an external audio signal based on using a multi-microphone speech generative network. The processor may also be configured to apply a first filter to an external audio signal, detected by at least one external microphone on the wearable device, during a listen through operation based on an activation of the audio zoom feature to generate a first listen-through signal that includes the external audio signal. The processor may be configured to produce an output audio signal that is based on at least the first listen-through signal that includes the external signal, and is based on the detected self-voice signal.

Separation of self-voice signal from a background signal using a speech generative network on a wearable device

A device includes one or more processors configured to perform signal processing including a linear transformation and a non-linear transformation of an input signal to generate a reference target signal. The reference target signal has a linear component associated with the linear transformation and a non-linear component associated with the non-linear transformation. The one or more processors are also configured to perform linear filtering of the input signal by controlling adaptation of the linear filtering to generate an output signal that substantially matches the linear component of the reference target signal.

Linearization of non-linearly transformed signals

A wearable device may include a processor configured to perform active noise cancelation (ANC) applied to an input audio signal received by at least one microphone, and detect a self-voice signal, based on one or more transducers. The processor may also be configured to apply a first filter to an external audio signal, detected by at least one external microphone on the wearable device, during a listen through operation based on an activation of the audio zoom feature to generate a first listen-through signal that includes the external audio signal. The processor may also be configured to after the activation of the audio zoom feature terminate a second filter that provides low frequency compensation. The processor may be configured to produce an output audio signal that is based on at least the first listen-through signal that includes the external signal, and is based on the detected self-voice signal.

Seamless listen-through based on audio zoom for a wearable device

Methods, systems, and devices for signal processing are described. Generally, as provided for by the described techniques, a wearable device may receive an input audio signal (e.g., including both an external signal and a self-voice signal). The wearable device may detect the self-voice signal in the input audio signal based on a self-voice activity detection (SVAD) procedure, and may implement the described techniques based thereon. The wearable device may perform beamforming operations or other separation procedures to isolate the external signal and the self-voice signal from the input audio signal. The wearable device may apply a first filter to the external signal, and a second filter to the self-voice signal. The wearable device may then mix the filtered signals, and generate an output signal that sounds natural to the user.

Seamless listen-through for a wearable device

An apparatus includes a processor configured to receive one or more media signals associated with a scene. The processor is also configured to identify a spatial location in the scene for each source of the one or more media signals. The processor is further configured to identify audio content for each media signal of the one or more media signals. The processor is also configured to determine one or more candidate spatial locations in the scene based on the identified spatial locations. The processor is further configured to generate audio to playback as virtual sounds that originate from the one or more candidate spatial locations.

Complementary virtual audio generation

Methods, systems, computer-readable media, and apparatuses for signal enhancement are presented. One example of such an apparatus includes a receiver configured to produce a remote speech signal from information carried by a wireless signal; a signal canceller configured to perform a signal cancellation operation on a local speech signal to generate a room response; and a filter configured to filter the remote speech signal according to the room response to produce a filtered speech signal. In this example, the signal cancellation operation is based on the remote speech signal as a reference signal.

Acoustic path modeling for signal enhancement

Methods, systems, and devices for signal processing are described. Generally, in one example as provided for by the described techniques, a wearable device includes a processor configured to retrieve a plurality of external microphone signals that includes audio sound from outside of the device from a memory; to separate, based on at least information from an internal microphone signal, a self-voice component from a background component; to perform a first listen-through operation on the separated self-voice component to produce a first listen-through signal; and to produce an output audio signal that is based on at least the first listen-through signal, wherein the output audio signal includes an audio zoom signal that includes audio sound of the plurality of external microphone signals.

A device includes a memory and one or more processors coupled to the memory. The one or more processors are configured to perform an active noise cancellation (ANC) operation on noisy input speech as captured by a first microphone, the noisy input speech as captured by a second microphone, or both, to suppress a noise level associated with the noisy input speech. The one or more processors are configured to match a second frequency spectrum of a second signal with a first frequency spectrum of a first signal. The first signal is representative of the noisy input speech as captured by the first microphone, and the second signal is representative of the noisy input speech as captured by the second microphone. The one or more processors are also configured to generate an output speech signal that is representative of input speech based on the second signal.

Noise suppression wearable device

Methods, systems, and devices for head-related transfer function generation are described. A device may receive a digital representation of a first audio signal associated with a location relative to a subject, and select from a database a first reference head-related transfer function measurement pair corresponding to the location of the first audio signal. The device may then obtain a second head-related transfer function measurement pair by performing a style transfer operation on the selected reference head-related transfer function measurement pair based on a set of head-related transfer function measurement pairs specific to the subject. As a result, the device may output a second audio signal based on the digital representation of the first audio signal and the second head-related transfer function measurement pair.

Head-related transfer function generation

Methods, systems, computer-readable media, and apparatuses for HRTF profile selection are presented. In one example, a device prompts a user to follow a simple procedure to obtain measurements that are matched to a suitable high-resolution HRTF profile.

Enabling a user to obtain a suitable head-related transfer function profile

Methods, systems, computer-readable media, and apparatuses for gesture control are presented. One example includes indicating, based on information from a first audio input signal, a presence of an object in proximity to a microphone, and increasing a volume level in response to the indicating.

Growing community of inventors

San Diego, CA, United States of America

Dongmei Wang