Showing papers on "Microphone published in 2012"

Adjusting a speech engine for a mobile computing device based on background noise

Abstract: Methods, apparatus, and products are disclosed for adjusting a speech engine for a mobile computing device based on background noise, the mobile computing device operatively coupled to a microphone, that include: sampling, through the microphone, background noise for a plurality of operating environments in which the mobile computing device operates; generating, for each operating environment, a noise model in dependence upon the sampled background noise for that operating environment; and configuring the speech engine for the mobile computing device with the noise model for the operating environment in which the mobile computing device currently operates.

An AlN MEMS Piezoelectric Microphone for Aeroacoustic Applications

Abstract: This paper describes the development of a micro- machined microphone for aircraft fuselage arrays that are utilized by aeroacousticians to help identify aircraft noise sources and/or assess the effectiveness of noise-reduction technologies. The developed microphone utilizes piezoelectric transduction via an integrated aluminum nitride layer in a thin-film composite diaphragm. A theoretical lumped element model and an associated noise model of the complete microphone system are developed and utilized in a formal design-optimization process. Optimal designs were fabricated using a variant of the film bulk acoustic resonator process at Avago Technologies. The experimental characterization of one design is presented here, and measured performance was in line with sponsor specifications, including a sensitivity of -39 μV/Pa, a minimum detectable pressure of 40.4 dB, a confirmed bandwidth up to 20 kHz, a 129.5-kHz resonant frequency, and a 3% distortion limit approaching 172 dB. With this performance-in addition to its small size-this microphone is shown to be a viable enabling technology for low-cost, high-resolution fuselage array measurements.

Field test of an affordable, portable, wireless microphone array for spatial monitoring of animal ecology and behaviour

Abstract: Summary 1. Using arrays of microphones, biologists can monitor the position of free-living animals based on the sounds they produce. Microphone array technology exploits differences in sound arrival times at each microphone to calculate an animal’s position. This technology provides new opportunities for studying animal ecology and behaviour and has many advantages over tracking technologies that require capturing animals and fitting them with external devices, or technologies that focus on one individual in isolation of the activities of nearby animals. 2. The efficacy of microphone arrays for triangulating the position of wild animals has been established through previous studies. Yet widespread use of microphone array technology has been limited by many factors: arrays are expensive, custom manufactured, and cumbersome. Consequently, microphone arrays are used infrequently, in spite of their transformative potential for studying animal ecology and behaviour. 3. We conducted a field test of a new wireless microphone array system that has multiple advantages over previous systems: it is relatively inexpensive, commercially available, includes an integrated global positioning system (GPS) for time-synchronizing microphones, and it is small enough to fit in a backpack. We set up an array of four stereo recorders (each with a pair of stereo microphones) at 12 sites and tested the system’s accuracy for estimating the location of loudspeakers broadcasting 25 types of bird, mammal and frog sounds. 4. We found that this system produced accurate location estimates based on multi-channel recordings of many types of acoustic signals. The average location accuracy was 1·87 ± 0·13 m, on par with cable-based microphone array systems. Location accuracy was significantly higher when the recorders were closer together and when sounds were broadcast inside the area bounded by the microphones. Accuracy tended to be higher in field vs. forest habitats. 5. We discuss how this system may be used to enhance studies of animal ecology and behaviour across a wide range of contexts. As with previous arrays, this system will allow researchers to monitor animals that produce distinctive acoustic signals. In contrast to previous microphone arrays, this system is affordable, portable and commercially available. Consequently, this system stands to dramatically enhance research on wild, free-living animals.

An Intelligent Food-Intake Monitoring System Using Wearable Sensors

Abstract: The prevalence of obesity worldwide presents a great challenge to existing healthcare systems. There is a general need for pervasive monitoring of the dietary behaviour of those who are at risk of co-morbidities. Currently, however, there is no accurate method of assessing the nutritional intake of people in their home environment. Traditional methods require subjects to manually respond to questionnaires for analysis, which is subjective, prone to errors, and difficult to ensure consistency and compliance. In this paper, we present a wearable sensor platform that autonomously provides detailed information regarding a subject's dietary habits. The sensor consists of a microphone and a camera and is worn discretely on the ear. Sound features are extracted in real-time and if a chewing activity is classified, the camera captures a video sequence for further analysis. From this sequence, a number of key frames are extracted to represent important episodes during the course of a meal. Results show a high classification rate of chewing activities, and the visual log demonstrates a detailed overview of the subject's food intake that is difficult to quantify from manually-acquired food records.

Mobile device having at least one microphone sensor and method for controlling the same

Abstract: A mobile device having at least one microphone sensor and a method for controlling the same are disclosed. The method includes receiving at least two audio signals through the at least one microphone sensor within a predetermined time period, recognizing input directions and voice command from the at least two audio signals sequentially, determining whether the recognized input directions and voice command match to preset input directions and preset voice command mapped to the preset directions, sequentially for the at least two received audio signals, and executing a preset control command, if the recognized input directions and voice command match to the preset input directions and voice command.

Adaptive voice recognition systems and methods

Abstract: A voice recognition system includes a microphone for receiving speech from a user and processing electronics. The processing electronics are in communication with the microphone and are configured to use a plurality of rules to evaluate user interactions with the voice recognition system. The processing electronics automatically determine and set an expertise level in response to and based on the evaluation. The processing electronics are configured to automatically adjust at least one setting of the voice recognition system in response to the set expertise level.

Microphone Array Processing for Distant Speech Recognition: From Close-Talking Microphones to Far-Field Sensors

Abstract: Distant speech recognition (DSR) holds the promise of the most natural human computer interface because it enables man-machine interactions through speech, without the necessity of donning intrusive body- or head-mounted microphones. Recognizing distant speech robustly, however, remains a challenge. This contribution provides a tutorial overview of DSR systems based on microphone arrays. In particular, we present recent work on acoustic beam forming for DSR, along with experimental results verifying the effectiveness of the various algorithms described here; beginning from a word error rate (WER) of 14.3% with a single microphone of a linear array, our state-of-the-art DSR system achieved a WER of 5.3%, which was comparable to that of 4.2% obtained with a lapel microphone. Moreover, we present an emerging technology in the area of far-field audio and speech processing based on spherical microphone arrays. Performance comparisons of spherical and linear arrays reveal that a spherical array with a diameter of 8.4 cm can provide recognition accuracy comparable or better than that obtained with a large linear array with an aperture length of 126 cm.

A Dual-Microphone Speech Enhancement Algorithm Based on the Coherence Function

Abstract: A novel dual-microphone speech enhancement technique is proposed in the present paper. The technique utilizes the coherence between the target and noise signals as a criterion for noise reduction and can be generally applied to arrays with closely spaced microphones, where noise captured by the sensors is highly correlated. The proposed algorithm is simple to implement and requires no estimation of noise statistics. In addition, it offers the capability of coping with multiple interfering sources that might be located at different azimuths. The proposed algorithm was evaluated with normal hearing listeners using intelligibility listening tests and compared against a well-established beamforming algorithm. Results indicated large gains in speech intelligibility relative to the baseline (front microphone) algorithm in both single and multiple-noise source scenarios. The proposed algorithm was found to yield substantially higher intelligibility than that obtained by the beamforming algorithm, particularly when multiple noise sources or competing talker(s) were present. Objective quality evaluation of the proposed algorithm also indicated significant quality improvement over that obtained by the beamforming algorithm. The intelligibility and quality benefits observed with the proposed coherence-based algorithm make it a viable candidate for hearing aid and cochlear implant devices.

Combining directional microphone and single-channel noise reduction algorithms: a clinical evaluation in difficult listening conditions with cochlear implant users.

Abstract: OBJECTIVES This study tested a combination of algorithms designed to improve cochlear implant performance in noise. A noise reduction (NR) algorithm, based on signal to noise ratio estimation was evaluated in combination with several directional microphone algorithms available in the Cochlear CP810 sound processor. DESIGN Fourteen adult unilateral cochlear implant users participated in the study. Evaluation was conducted using word recognition in quiet, sentence recognition in noise, and subjective feedback via questionnaire after a period of take-home use. Music appreciation was also evaluated in a controlled listening task. The sentence recognition task measured speech reception threshold for 50% morphemes correct. The interfering maskers were speech-weighted noise and competing talkers, which were spatially separated from the target speech. In addition, the locations of the noise maskers changed during the test in an effort to replicate relevant real-world listening conditions. SmartSound directionality settings Standard, Zoom, and Beam (used in the SmartSound programs Everyday, Noise, and Focus, respectively) were all evaluated with and without NR. RESULTS Microphone directionality demonstrated a consistent benefit in sentence recognition in all noise conditions tested. The group average speech reception threshold benefit over the Standard setting was 3.7 dB for Zoom and 5.3 dB for Beam. Addition of the NR algorithm further improved sentence recognition by 1.3 dB when the noise maskers were speech-weighted noise. There was an overall group preference for the NR algorithm in noisy environments. Group mean word recognition in quiet, preference in quiet conditions, and music appreciation were all unaffected by the NR algorithm. CONCLUSIONS Multimicrophone directionality was effective in improving speech understanding in spatially separated noisy conditions. The single-channel NR algorithm further enhanced speech intelligibility in speech-weighted noise for cochlear implant users while maintaining equivalent performance in quiet situations and when listening to music.

Noise reduction for dual-microphone mobile phones exploiting power level differences

Abstract: This paper discusses the application of noise reduction algorithms for dual-microphone mobile phones. An analysis of the acoustical environment based on recordings with a dual-microphone mock-up phone mounted on a dummy head is given. Motivated by the recordings, a novel dual-channel noise reduction algorithm is proposed. The key components are a noise PSD estimator and an improved spectral weighting rule which both explicitly exploit the Power Level Differences (PLD) of the desired speech signal between the microphones. Experiments with recorded data show that this low complexity system has a good performance and is beneficial for an integration into future mobile communication devices.

Active noise cancellation decisions using a degraded reference

Abstract: Active noise cancellation (ANC) circuitry is coupled to the input of an earpiece speaker in a portable audio device, to control the ambient acoustic noise outside of the device and that may be heard by a user of the device. A microphone is to pickup sound emitted from the earpiece speaker, as well as the ambient acoustic noise. Control circuitry deactivates the ANC in response to determining that an estimate of how much sound emitted from the earpiece speaker has been corrupted by noise indicates insufficient corruption by noise. In another embodiment, the ANC decision is in response to determining that an estimate of the ambient acoustic noise level is greater than an estimate of the anti-noise produced by the ANC. Other embodiments are also described and claimed.

Ear-coupling detection and adjustment of adaptive response in noise-canceling in personal audio devices

Abstract: A personal audio device, such as a wireless telephone, includes an adaptive noise canceling (ANC) circuit that adaptively generates an anti-noise signal from a reference microphone signal and injects the anti-noise signal into the speaker or other transducer output to cause cancellation of ambient audio sounds. An error microphone is also provided proximate the speaker to estimate an electro-acoustical path from the noise canceling circuit through the transducer. A processing circuit determines a degree of coupling between the user's ear and the transducer and adjusts the adaptive cancellation of the ambient sounds to prevent erroneous and possibly disruptive generation of the anti-noise signal if the degree of coupling lies either below or above a range of normal operating ear contact pressure.

Bandlimiting anti-noise in personal audio devices having adaptive noise cancellation (ANC)

Abstract: A personal audio device, such as a wireless telephone, includes noise canceling circuit that adaptively generates an anti-noise signal from a reference microphone signal and injects the anti-noise signal into the speaker or other transducer output to cause cancellation of ambient audio sounds. An error microphone may also be provided proximate the speaker to measure the output of the transducer in order to control the adaptation of the anti-noise signal and to estimate an electro-acoustical path from the noise canceling circuit through the transducer. A processing circuit that performs the adaptive noise canceling (ANC) function also either adjusts the frequency response of the anti-noise signal with respect to the reference microphone signal, and/or by adjusting the response of the adaptive filter independent of the adaptation provided by the reference microphone signal.

Adaptive noise canceling architecture for a personal audio device

Abstract: A personal audio device, such as a wireless telephone, includes an adaptive noise canceling (ANC) circuit that adaptively generates an anti-noise signal from a reference microphone signal that measures the ambient audio and an error microphone signal that measures the output of an output transducer plus any ambient audio at that location and injects the anti-noise signal at the transducer output to cause cancellation of ambient audio sounds. A processing circuit uses the reference and error microphone to generate the anti-noise signal, which can be generated by an adaptive filter operating at a multiple of the ANC coefficient update rate. Downlink audio can be combined with the high data rate anti-noise signal by interpolation. High-pass filters in the control paths reduce DC offset in the ANC circuits, and ANC coefficient adaptation can be halted when downlink audio is not detected.

Signal processing device and signal processing method

Abstract: There is provided a signal processing device s including a noise cancellation process clock generation unit configured to generate a noise cancellation process clock having a predetermined fixed frequency, a noise canceling unit configured to include a noise canceling filter operating based on the noise cancellation process clock and generating a noise canceling signal having a signal property of canceling an external noise component based on an input audio signal including the external noise component picked up by a microphone, and an addition unit superimposing the noise canceling signal generated by the filter on a digital audio signal, and a sampling rate conversion unit configured to rate-convert the input digital audio signal sampled at a clock in asynchrony with the noise cancellation process clock to a signal at a sampling frequency in synchrony with the noise cancellation process clock and to supply the rate-converted signal to the addition unit.

Monitoring volcanic activity using correlation patterns between infrasound and ground motion

Abstract: [1] This paper presents a simple method to distinguish infrasonic signals from wind noise using a cross-correlation function of signals from a microphone and a collocated seismometer. The method makes use of a particular feature of the cross-correlation function of vertical ground motion generated by infrasound, and the infrasound itself. Contribution of wind noise to the correlation function is effectively suppressed by separating the microphone and the seismometer by several meters because the correlation length of wind noise is much shorter than wavelengths of infrasound. The method is applied to data from two recent eruptions of Asama and Shinmoe-dake volcanoes, Japan, and demonstrates that the method effectively detects not only the main eruptions, but also minor activity generating weak infrasound hardly visible in the wave traces. In addition, the correlation function gives more information about volcanic activity than infrasound alone, because it reflects both features of incident infrasonic and seismic waves. Therefore, a graphical presentation of temporal variation in the cross-correlation function enables one to see qualitative changes of eruptive activity at a glance. This method is particularly useful when available sensors are limited, and will extend the utility of a single microphone and seismometer in monitoring volcanic activity.

Method of identifying a wireless communication channel in a sound system

Abstract: A method of identifies an appropriate wireless communication channel in an audio receiving device, that comprises 1) a wireless receiver receiving an audio signal on a particular transmission channel selected among a predefined number of possible transmission channels, and 2) a microphone for picking up a sound in the environment of the audio receiving device. The method comprises a) selecting a channel as the receiving channel among a predefined number of possible transmission channels; b) analyzing the received signal received and the signal picked up by the microphone; c) determining whether a predefined criterion concerning the degree of similarity of the received signal and the signal picked up by the microphone is fulfilled; d) KEEPING the channel as the receiving channel, if the predefined criterion is fulfilled; and e) CHANGING the receiving channel to another channel if the predefined criterion is NOT fulfilled.

Loudspeaker beamforming for personal audio focal points

Abstract: In one embodiment, a method comprising receiving at a microphone located at a first location audio received from plural speakers, the audio received at a first amplitude level; and responsive to moving the microphone away from the first location to a second location, causing adjustment of the audio provided by the plural speakers to target the first amplitude level at the microphone.

Acoustic analysis by spherical microphone array processing of room impulse responses

Abstract: Spherical microphone arrays have been recently used for room acoustics analysis, to detect the direction-of-arrival of early room reflections, and compute directional room impulse responses and other spatial room acoustics parameters. Previous works presented methods for room acoustics analysis using spherical arrays that are based on beamforming, e.g., delay-and-sum, regular beamforming, and Dolph-Chebyshev beamforming. Although beamforming methods provide useful directional selectivity, optimal array processing methods can provide enhanced performance. However, these algorithms require an array cross-spectrum matrix with a full rank, while array data based on room impulse responses may not satisfy this condition due to the single frame data. This paper presents a smoothing technique for the cross-spectrum matrix in the frequency domain, designed for spherical microphone arrays, that can solve the problem of low rank when using room impulse response data, therefore facilitating the use of optimal array processing methods. Frequency smoothing is shown to be performed effectively using spherical arrays, due to the decoupling of frequency and angular components in the spherical harmonics domain. Experimental study with data measured in a real auditorium illustrates the performance of optimal array processing methods such as MUSIC and MVDR compared to beamforming.

Methods, apparatuses and computer program products for facilitating directional audio capture with multiple microphones

Abstract: An apparatus for providing directional audio capture may include a processor and memory storing executable computer program code that cause the apparatus to at least perform operations including assigning at least one beam direction, among a plurality of beam directions, in which to direct directionality of an output signal of one or more microphones. The computer program code may further cause the apparatus to divide microphone signals of the microphones into selected frequency subbands wherein an analysis performed. The computer program code may further cause the apparatus to select at least one set of microphones of the apparatus for selected frequency subbands. The computer program code may further cause the apparatus to optimize the assigned at least one beam direction by adjusting a beamformer parameter(s) based on the selected set of microphones and at least one of the selected frequency subbands. Corresponding methods and computer program products are also provided.

Hybrid adaptive headphone

Abstract: An adaptive noise-cancelling headphone including an earcup housing having a driver for outputting sound to a user positioned therein. The headphone further including an active noise control assembly. The active noise control assembly may include an ambient microphone capable of detecting an ambient noise outside of the housing and an error microphone capable of detecting an earcup noise inside of the housing. Based on the detected noise, active noise cancellation within the headphone is either enabled or disabled. The headphone may further include a passive noise control assembly. The passive noise control assembly may include an acoustic valve associated with an acoustic vent formed within the earcup housing. The acoustic valve is capable of being modified between an open configuration to decrease sound attenuation and a closed configuration to increase sound attenuation in response to the detected ambient noise so as to improve an acoustic performance of the earcup.

Portable electronic device

Abstract: According to one embodiment, a portable electronic device includes a touch-screen display The electronic device executes a function which is associated with a display object corresponding to a tap position on the touch-screen display The electronic device includes at least one microphone, a speech processing module configured to process an input speech signal from the at least one microphone, and a translation result output module configured to output a translation result of a target language The translation result of the target language is obtained by recognizing and machine-translating the input speech signal which is processed by the speech processing module The speech processing module detects a tap sound signal in the input speech signal, the tap sound signal being produced by tapping the touch-screen display, and corrects the input speech signal in order to reduce an influence of the detected tap sound signal upon the input speech signal

Methods and apparatuses for multiple configurations of beamforming microphone arrays

Abstract: Embodiments include methods and apparatuses for sensing acoustic waves for a conferencing application. A conferencing apparatus includes a plurality of directional microphones oriented to cover a corresponding plurality of direction vectors and disposed in a housing. An orientation sensor is configured to generate an orientation signal indicative of an orientation of the housing. A processor is operably coupled to the plurality of directional microphones and the orientation sensor. The processor is configured to automatically adjust a signal processing characteristic of one or more directional microphones of the plurality of directional microphones responsive to the orientation signal.

Microphone system with a hand-held microphone

Abstract: A microphone system is provided. The microphone system comprises at least one hand-held microphone (100) and a base station (200). Audio signals detected by the hand-held microphone (100) are forwarded to the base station (200). The hand-held microphone (100) comprises a motion detection unit (122) for detecting a motion or a gesture of a hand-held microphone (100). A control signal generating unit generates control signals based on the detected motion or gesture of the hand-held microphone (100). The hand-held microphone (100) is adapted to forward the detected motion or gesture or the control signals to the base station (200). The output audio signal of the hand-held microphone (100) can be manipulated based on the control signals. The hand-held microphone (100) comprises an activation unit (130) for activating or deactivating the motion detection unit (122) or for activating or deactivating the transmission of the control signals.

Method and system for obtaining an audio signal

Abstract: A method and system for obtaining an audio signal. In one embodiment, the method comprises receiving a first sound signal at a first microphone arranged at a first height vertically above a substantially flat surface; receiving a second sound signal at a second microphone arranged at a second height vertically above the substantially flat surface; processing a signal provided by the first microphone using a low pass filter; processing a signal provided by the second microphone using a high pass filter; adding the signals processed by the low pass filter and the high pass filter to form a sum signal; and outputting the sum signal as an audio signal.

Leakage-modeling adaptive noise canceling for earspeakers

Abstract: A personal audio device, such as a headphone, includes an adaptive noise canceling (ANC) circuit that adaptively generates an anti-noise signal from a reference microphone signal that measures the ambient audio, and the anti-noise signal is combined with source audio to provide an output for a speaker. The anti-noise signal causes cancellation of ambient audio sounds that appear at the reference microphone. A processing circuit uses the reference microphone to generate the anti-noise signal, which can be generated by an adaptive filter. The processing circuit also models an acoustic leakage path from the transducer to the reference microphone and removes elements of the source audio appearing at the reference microphone signal due to the acoustic output of the speaker. Another adaptive filter can be used to model the acoustic leakage path.

Geometrically Constrained Room Modeling With Compact Microphone Arrays

Abstract: The geometry of an acoustic environment can be an important information in many audio signal processing applications. To estimate such a geometry, previous work has relied on large microphone arrays, multiple test sources, moving sources or the assumption of a 2-D room. In this paper, we lift these requirements and present a novel method that uses a compact microphone array to estimate a 3-D room geometry, delivering effective estimates with low-cost hardware. Our approach first probes the environment with a known test signal emitted by a loudspeaker co-located with the array, from which the room impulse responses (RIRs) are estimated. It then uses an l1-regularized least-squares minimization to fit synthetically generated reflections to the RIRs, producing a sparse set of reflections. By enforcing structural constraints derived from the image model, these are classified into first-, second-, and third-order reflections, thereby deriving the room geometry. Using this method, we detect walls using off-the-shelf teleconferencing hardware with a typical range resolution of about 1 cm. We present results using simulations and data from real environments.

Audio localization using audio signal encoding and recognition

Abstract: A positioning network comprises an array of signal sources that transmit signals with unique characteristics that are detectable in signals captured through a sensor on a mobile device, such as a microphone of a mobile phone handset. Through signal processing of the captured signal, the positioning system distinguishes these characteristics to identify distinct sources and their corresponding coordinates. A position calculator takes these coordinates together with other attributes derived from the received signals from distinct sources, such as time of arrival or signal strength, to calculate coordinates of the mobile device. A layered protocol is used to introduce distinguishing characteristics in the source signals. This approach enables the use of low cost components to integrate a positioning network on equipment used for other functions, such as audio playback equipment at shopping malls and other venues where location based services are desired.