Abstract: Methods for voice sensing and keyword analysis are provided. An example method allows for causing a mobile device to transition to a second power mode, from a first power mode, in response to a first acoustic signal. The method includes authenticating a user based at least in part on a second acoustic signal. While authenticating the user, the second acoustic signal is compared to a spoken keyword. The spoken keyword is analyzed for authentication strength based on the length of the spoken keyword, quality of a series of phonemes used to represent the spoken keyword, and likelihood of the series of phonemes to be detected by a voice sensing. While receiving the first and second acoustic signals, a signal to noise ratio (SNR) is determined. The SNR is used to adjust sensitivity of a detection threshold of a voice sensing.

Abstract: A single-stage buffer apparatus includes a first transistor, a second transistor, and a high pass filter network. The first transistor is configured to receive an input signal from a microphone. The second transistor is configured to operate as a cascode transistor. The high pass filter network is coupled to the first transistor and the second transistor. The second transistor electrically decouples the first transistor from an output of the single-stage buffer apparatus. A gate terminal of the second transistor is driven by the high-pass filter network, and the high-pass filter network is driven by the first transistor.

Abstract: At a microphone, voice activity is detected in a data stream while simultaneously buffering audio data from the data stream to create buffered data. A signal is sent to a host indicating the positive detection of voice activity in the data stream. When an external clock signal is received from the host, the internal operation of the microphone is synchronized with the external clock signal. Buffered data stream is selectively sent through a first path, the first path including a buffer having a buffer delay time representing the time the first data stream takes to move through the buffer. The data stream is continuously sent through a second path as a real-time data stream, the second path not including the buffer, the real-time data stream beginning with the extended buffer data at a given instant in time. The buffered data stream and the real-time data stream are multiplexed onto a single data line and transmitting the multiplexed data stream to the host.

Abstract: A microphone that includes a calibration signal generator that generates a calibration signal based upon a received invocation input. The calibration signal has known audio properties. The microphone also includes a transducer that converts sound energy into an electrical signal. An integrated circuit receives the electrical signal from the transducer. An external microphone interface provides the calibration signal to a device external to the microphone.

Abstract: A device includes a first microelectromechanical systems (MEMS) transducer, a second MEMS transducer and a summing device. A first dimension of the first MEMS transducer is predefined to configure the first MEMS transducer to have a first resonance frequency. A second dimension of the second MEMS transducer is predefined to configure the second MEMS transducer to have a second resonance frequency different than the first resonance frequency. The summing device is coupled to the first MEMS transducer and the second MEMS transducer and provides an output representing a combination of information from the first MEMS transducer and the second MEMS transducer.

Abstract: An acoustic apparatus includes a first digital microphone having a first clock pin, a second digital microphone having a second clock pin, an application processor having a third clock pin, a first interface that couples the first digital microphone and the application processor, and a second interface that couples the first digital microphone, the second digital microphone, and the application processor. The acoustic apparatus further includes a clock that connects to the first clock pin, the second clock pin, and the third clock pin, wherein first data is transmitted on a first clock edge, and wherein second, different data is transmitted on a second other clock edge.

Abstract: A hearing instrument includes a first speaker having a first frequency range. The hearing instrument also includes a second speaker that is disposed in the ear of a listener. The second speaker has a second frequency range that is wider than the first frequency range. A microphone unit is coupled to the first speaker and the second speaker. The first speaker creates replacement sounds within the first frequency range that replicate sounds that are lost to the listener as a result of an occlusion effect at the second speaker. The replacement sounds are presented to the listener.

Abstract: A receiver apparatus includes a first receiver portion and an acoustic filter network. The first receiver portion has a housing and is configured to convert at least one electrical signal into first sound energy having a first frequency range. The acoustic filter network communicates with the first receiver portion and is configured to receive the first sound energy. The acoustic filter network includes at least one sound channel and at least one chamber that communicates with the at least one sound channel. The least one sound channel includes a main branch and a first side branch and the at least one chamber comprises a first chamber. The first side branch communicates with the main branch and the first chamber, and the main branch is configured to receive the first sound energy.

Abstract: Noise suppression information is used to optimize or improve automatic speech recognition performed for a signal. Noise suppression can be performed on a noisy speech signal using a gain value. The gain to apply to the noisy speech signal is selected to optimize speech recognition analysis of the resulting signal. The gain may be selected based on one or more features for a current sub band and time frame, as well as one or more features for other sub bands and/or time frames. Noise suppression information can be provided to a speech recognition module to improve the robustness of the speech recognition analysis. Noise suppression information can also be used to encode and identify speech.

Abstract: Various embodiments relating to microphone with integrated sensor are disclosed herein. In one implementation, a sensor is disposed in, on, integrated with, and/or at the lid of a micro electro mechanical system (MEMS) microphone. In another implementation, a sensor is disposed at or integrated with an insert, over which a micro electro mechanical system (MEMS) device is disposed in a MEMS microphone. In disposing the sensor at the lid or insert, significant space savings are achieved. Consequently, a small-sized microphone is provided and achieved allowing the microphone deployed in applications where miniaturization is required or advantageous.

Abstract: A microphone includes a base, a MEMS device, and an integrated circuit. The MEMS device includes a diaphragm and a back plate. The MEMS device is connected to the integrated circuit. The microphone also includes a pressure sensor. A lid enclosed the MEMS device and the integrated circuit.

Abstract: A microphone device is comprises a first micro electro mechanical system (MEMS) device and a second MEMS device with difference size of pierce holes in the diaphragms. Signal outputs from the first and second MEMS devices are selectively used to provide wind noise resistance.

Abstract: A microphone includes a base, a MEMS device, and an integrated circuit. The MEMS device includes a diaphragm and a back plate. The MEMS device is connected to the integrated circuit. The microphone also includes a temperature sensor. A lid enclosed the MEMS device and the integrated circuit.

Abstract: A microphone includes a base, a micro electro mechanical system (MEMS) device disposed on the base, and a front end processing apparatus disposed on the base and coupled to the MEMS device, the front end processing apparatus being configured to convert analog signals received from the MEMS device into digital signals. The microphone also includes a DSP apparatus, the DSP apparatus being a digital programmed device with a computer memory, the DSP apparatus configured to process the digital signals received from the front end processing apparatus. The MEMS device, the front end processing apparatus, and DSP apparatus are enclosed within a single microphone enclosure or assembly. During operation the DSP apparatus generates DSP noise. The DSP apparatus includes a noise reduction structure that substantially prevents the DSP noise from reaching or interfering with the operation of the MEMS device or the front end processing apparatus.

Abstract: Provided are systems and methods for generating clean speech from a speech signal representing a mixture of a noise and speech. The clean speech may be generated from synthetic speech parameters. The synthetic speech parameters are derived based on the speech signal components and a model of speech using auditory and speech production principles. The modeling may utilize a source-filter structure of the speech signal. One or more spectral analyzes on the speech signal are performed to generate spectral representations. The feature data is derived based on a spectral representation. The features corresponding to the target speech according to a model of speech are grouped and separated from the feature data. The synthetic speech parameters, including spectral envelope, pitch data and voice classification data are generated based on features corresponding to the target speech.

Abstract: Systems and methods for real time monitoring of acoustic environment using ultrasound are provided. An example method includes causing production of an acoustic sensing signal. The acoustic sensing signal can be a continuously repeating ultrasonic signal. The method further includes receiving a reflected acoustic signal, the reflected acoustic signal being a representation of an acoustic signal reflected within the acoustic environment. The method further includes analyzing the reflected acoustic signal based at least in part on the acoustic sensing signal to determine properties of the acoustic environment. The acoustic sensing signal can be produced based on a pseudorandom binary sequence. Analyzing the reflected acoustic signal includes correlating the reflected acoustic signal and the acoustic sensing signal to determine a real time estimate of impulse response of the acoustic environment. The method further allows determining that the properties of the acoustic environment have changed.

Abstract: An acoustic sensing apparatus includes a diaphragm; a support structure surrounding the diaphragm and a gap disposed there between, the diaphragm and support structure separating a front volume and a back volume; one or more cantilevers disposed in the gap and between the diaphragm and the support structure, a first end of each of the cantilevers coupled to the support structure and being non-moving, and a second end of each of the cantilevers being free to move; a sealing material covering at least the gap between the diaphragm and the support structure, the sealing material creating an acoustic seal between the front volume and the back volume; and a sensor that converts a diaphragm movement into an electrical signal. The second end of each of the cantilevers is coupled to the sealing material.

Abstract: Microphone devices are disclosed. The microphone device includes a base, a lid, a side wall between the base and the lid, and a MEMS die. The side wall includes a first portion with a first width and a second portion with a second width disposed under the first portion. The first width is less than the second width such that a shoulder is formed on the second portion. The MEMS die is supported on the shoulder. The MEMS die includes a diaphragm and a back plate.

Abstract: Provided are methods and systems for continuous voice sensing. An example method allows for detecting and buffering, by a first module, a key phrase in an acoustic signal. Responsive to the detection, the method includes sending an interrupt to a second module and switching the first module to an omnidirectional microphone mode. Upon receiving the interrupt, the second module is operable to boot up from a low power mode to an operational mode. While the second module is booting up, the first module is operable to continue to buffer a clean speech output generated from an acoustic signal captured by at least one omnidirectional microphone. After the second module is booted, an indication may be sent to the first module that the second module is ready to exchange data through a fast connection. Upon receiving the indication, the buffered clean speech output may be sent to the second module.

Abstract: Systems and methods for estimating and tracking multiple attributes of multiple objects from multi-sensor data are provided. An exemplary method includes identifying features associated with sensor data. The sensor data represents data captured by at least one of a plurality of acoustic and non-acoustic sensors. Identification of the features associated with the sensor data may be based variously on detected sounds, motions, images, and the like. The exemplary method further includes determining, in parallel, multiple probable objects based at least in part on the identified features. Various embodiments of the method also include forming hypotheses based at least in part on associating identified features with the multiple probable objects and attributing the formed hypotheses to channels. Sequence of the formed hypotheses are constructed.