Abstract: The headset comprises: a physiological sensor suitable for being coupled to the cheek or the temple of the wearer of the headset and for picking up non-acoustic voice vibration transmitted by internal bone conduction; lowpass filter means for filtering the signal as picked up; a set of microphones picking up acoustic voice vibration transmitted by air from the mouth of the wearer of the headset; highpass filter means and noise-reduction means for acting on the signals picked up by the microphones; and mixer means for combining the filtered signals to output a signal representative of the speech uttered by the wearer of the headset. The signal of the physiological sensor is also used by means for calculating the cutoff frequency of the lowpass and highpass filters and by means for calculating the probability that speech is absent.

Abstract: A method of encoding a low bit-rate audio signal includes quantizing and encoding a plurality of low frequency sub-bands of an audio signal in a frequency domain, generating a codebook of codevectors using sub-bands of the audio signal spectrum, detecting an envelope of another frequency sub-band of the audio signal and quantizing and losslessly-encoding the detected envelope, selecting a codevector most similar to the higher frequency sub-band spectrum from the generated codebook's codevectors and determining its codebook codevector index, and generating a bit stream.

Abstract: A voice activity detection method and apparatus, and an electronic device are provided. The method includes: obtaining a time domain parameter and a frequency domain parameter from an audio frame; obtaining a first distance between the time domain parameter and a long-term sliding mean of the time domain parameter in a history background noise frame, and obtaining a second distance between the frequency domain parameter and a long-term sliding mean of the frequency domain parameter in the history background noise frame; and judging whether the audio frame is a foreground voice frame or a background noise frame according to the first distance, the second distance and a set of decision inequalities based on the first distance and the second distance. The above technical solutions enable the judgment criterion to have an adaptive adjustment capability, thus improving the performance of the voice activity detection.

Abstract: A noise cancellation apparatus includes a noise estimation module for receiving a noise-containing input speech, and estimating a noise therefrom to output the estimated noise; a first Wiener filter module for receiving the input speech, and applying a first Wiener filter thereto to output a first estimation of clean speech; a database for storing data of a Gaussian mixture model for modeling clean speech; and an MMSE estimation module for receiving the first estimation of clean speech and the data of the Gaussian mixture model to output a second estimation of clean speech. The apparatus further includes a final clean speech estimation module for receiving the second estimation of clean speech from the MMSE estimation module and the estimated noise from the noise estimation module, and obtaining a final Wiener filter gain therefrom to output a final estimation of clean speech by applying the final Wiener filter gain.

Abstract: A signal processing device includes a bass signal extractor, a harmonic wave generator, a level detector, and an adjustment controller. The bass signal extractor first extracts a bass signal from an input audio signal. Natural-sounding bass enhancement is achieved as a result of the adjustment controller boosting the bass signal level until the level detector detects the bass signal level at a set level. For input bass signal levels higher than the set level, bass is enhanced virtually using a harmonic signal generated from the bass signal by the harmonic wave generator. As a result, the disadvantages of the boost method and the virtual signal enhancement method are mutually compensated for, and synergistic advantages for bass enhancement are obtained.

Abstract: Psychoacoustic Bass Enhancement (PBE) is integrated with one or more other audio processing techniques, such as active noise cancellation (ANC), and/or receive voice enhancement (RVE), leveraging each technique to achieve improved audio output. This approach can be advantageous for improving the performance of headset speakers, which often lack adequate low-frequency response to effectively support ANC.

Abstract: An adaptive audio system can be implemented in a communication device. The adaptive audio system can enhance voice in an audio signal received by the communication device to increase intelligibility of the voice. The audio system can adapt the audio enhancement based at least in part on levels of environmental content, such as noise, that are received by the communication device. For higher levels of environmental content, for example, the audio system might apply the audio enhancement more aggressively. Additionally, the adaptive audio system can detect substantially periodic content in the environmental content. The adaptive audio system can further adapt the audio enhancement responsive to the environmental content.

Abstract: A voice command acquisition method and system for motor vehicles is improved in that noise source information is obtained directly from the vehicle system bus. Upon receiving an input signal with a voice command, the system bus is queried for one or more possible sources of a noise component in the input signal. In addition to vehicle-internal information (e.g., window status, fan blower speed, vehicle speed), the system may acquire external information (e.g., weather status) in order to better classify the noise component in the input signal. If the noise source is found to be a window, for example, the driver may be prompted to close the window. In addition, if the fan blower is at a high speed level, it may be slowed down automatically.

Abstract: An audio signal is conveyed more efficiently by transmitting or recording a baseband of the signal with an estimated spectral envelope and a noise-blending parameter derived from a measure of the signal's noise-like quality. The signal is reconstructed by translating spectral components of the baseband signal to frequencies outside the baseband, adjusting phase of the regenerated components to maintain phase coherency, adjusting spectral shape according to the estimated spectral envelope, and adding noise according to the noise-blending parameter. Preferably, the transmitted or recorded signal also includes an estimated temporal envelope that is used to adjust the temporal shape of the reconstructed signal.

Abstract: Electronic devices and accessories are provided that may communicate over wired communications paths. The electronic devices may be portable electronic devices such as cellular telephones or media players and may have audio connectors such as 3.5 mm audio jacks. The accessories may be headsets or other equipment having mating 3.5 mm audio plugs and speakers for playing audio. Microphones may be included in an accessory to gather voice signals and noise cancellation signals. Analog-to-digital converter circuitry in the accessory may digitize the microphone signals. Digital voice signals and voice noise cancellation signals can be transmitted over the communications path and processed by audio digital signal processor circuitry in an electronic device. Digital-to-analog converter circuitry in the accessory may convert digital audio signals to analog speaker signals.

Abstract: A system for combining signals includes a first microphone generating a first input signal having a first voice component and a first noise component, a second microphone generating a second input signal having a second voice component and a second noise component, a mixing circuit, and an adaptive filter. The mixing circuit applies a first gain having a value ? to the first input signal to produce a first scaled signal, applies a second gain having a value 1?? to the second input signal to produce a second scaled signal, and sums the first scaled signal and the second scaled signal to produce a summed signal. The adaptive filter computes an updated value of ? to minimize the energy of the summed signal based on the summed signal, the first input signal and the second input signal, and provides the updated value of ? to the mixing circuit.

Abstract: A speech enhancement method operative for devices having limited available memory is described. The method is appropriate for very noisy environments and is capable of estimating the relative strengths of speech and noise components during both the presence as well as the absence of speech.

Abstract: A method (400, 600, 700) and apparatus (220) for enhancing the intelligibility of speech emitted into a noisy environment. After filtering (408) ambient noise with a filter (304) that simulates the physical blocking of noise by a at least a part of a voice communication device (102) a frequency dependent SNR of received voice audio relative to ambient noise is computed (424) on a perceptual (e.g. Bark) frequency scale. Formants are identified (426, 600, 700) and the SNR in bands including certain formants are modified (508, 510) with formant enhancement gain factors in order to improve intelligibility. A set of high pass filter gains (338) is combined (516) with the formant enhancement gains factors yielding combined gains which are clipped (518), scaled (520) according to a total SNR, normalized (526), smoothed across time (530) and frequency (532) and used to reconstruct (532, 534) an audio signal.

Abstract: In a noise reduction apparatus for controlling noise up to a predetermined upper limited frequency, a distance from a noise source to control point X is made larger than a distance obtained by subtracting a one-half wavelength from a distance, obtained by adding up a distance from the noise source to a noise detecting microphone, a distance corresponding to time as a sum of respective delay time of the noise detecting microphone, a noise controller, and a control speaker, and a distance from the control speaker to control point X, where one wavelength is a period corresponding to the upper limited frequency.

Abstract: An apparatus for processing an audio signal and method thereof are disclosed, by which a local dynamic range of an audio signal can be adaptively normalized as well as a maximum dynamic range of the audio signal. The present invention includes receiving a signal, by an audio processing apparatus; computing a long-term power and a short-term power by estimating power of the signal; generating a slow gain based on the long-term power; generating a fast gain based on the short-term power; obtaining a final gain by combining the slow gain and the fast gain; and, modifying the signal using the final gain.

Abstract: The present invention relates to a continuous speech recognition system that is very robust in a noisy environment. In order to recognize continuous speech smoothly in a noisy environment, the system selects call commands, configures a minimum recognition network in token, which consists of the call commands and mute intervals including noises, recognizes the inputted speech continuously in real time, analyzes the reliability of speech recognition continuously and recognizes the continuous speech from a speaker. When a speaker delivers a call command, the system for detecting the speech interval and recognizing continuous speech in a noisy environment through the real-time recognition of call commands measures the reliability of the speech after recognizing the call command, and recognizes the speech from the speaker by transferring the speech interval following the call command to a continuous speech-recognition engine at the moment when the system recognizes the call command.

Abstract: An apparatus for processing an audio signal and method thereof are disclosed, by which a local dynamic range of an audio signal can be adaptively normalized as well as a maximum dynamic range of the audio signal. The present invention includes receiving, by an audio processing apparatus, a signal, and feedback information estimated based on a normalizing gain; generating a noise estimation based on the signal; computing a gain filter for noise canceling, based on the noise estimation and the signal; and, obtaining a restricted gain filter by applying the feedback information to the gain filter.

Abstract: A method of and apparatus for detecting noise are provided. The method of detecting noise includes: receiving an input of a voice frame and converting the voice frame into a filter bank vector; converting the converted filter bank vector into band data; calculating a weight Gaussian mixture model (GMM) for each band by using the converted band data; and detecting noise in the voice frame based on the calculation result.

Abstract: A noise reduction system and a noise reduction method are provided. The noise reduction system comprises a uni-directional microphone, an omni-directional microphone and a signal processing module. The signal processing module comprises an adaptive noise control (ANC) unit, a main noise reduction unit and an optimizing unit. The uni-directional microphone senses a first audio source to output a first audio signal, and the omni-directional microphone senses a second audio source to output a second audio signal. The ANC unit executes an adaptive noise control to output an estimated signal according to the first audio signal and the second audio signal. The main noise reduction unit executes a main noise reduction process to output a de-noise speech signal according to the estimated signal and the second audio signal. The optimizing unit executes an optimizing process to output an optimized speech signal according to the de-noise speech signal.

Abstract: A method for processing sound that includes, generating one or more noise component estimates relating to an electrical representation of the sound and generating an associated confidence measure for the one or more noise component estimates. The method further comprises processing, based on the confidence measure, the sound.

Abstract: The invention relates to audio signal processing. More specifically, the invention relates to enhancing multichannel audio, such as television audio, by applying a gain to the audio that has been smoothed between segments of the audio. The invention relates to methods, apparatus for performing such methods, and to software stored on a computer-readable medium for causing a computer to perform such methods.

Abstract: A speech enhancement system improves the perceptual quality of a processed voice signal. The system improves the perceptual quality of a voice signal by removing unwanted noise components from a voice signal. The system removes undesirable signals that may result in the loss of information. The system receives and analyzes signals to determine whether an undesired random or persistent signal corresponds to one or more modeled noises. When one or more noise components are detected, the noise components are substantially removed or dampened from the signal to provide a less noisy voice signal.

Abstract: According to an aspect of the invention, there is provided a noise suppressing apparatus comprising: a fifth unit configured to calculate a gain for noise suppression, based on the first signal-to-noise ratio for each frequency band and the second signal-to-noise ratio for an entire frequency band; an eighth unit configured to calculate an upper limit value of a noise suppression amount for each frequency band, based on the second signal-to-noise ratio; a ninth unit configured to calculate the noise suppression amount for each frequency band, based on the first signal-to-noise ratio; and a tenth unit configured to limit, based on the upper limit value, the noise suppression amount so as to calculate the gain.

Abstract: A model application unit calculates linear prediction coefficients of a multi-step linear prediction model by using discrete acoustic signals. Then, a late reverberation predictor calculates linear prediction values obtained by substituting the linear prediction coefficients and the discrete acoustic signals into linear prediction term of the multi-step linear prediction model, as predicted late reverberations. Next, a frequency domain converter converts the discrete acoustic signals to discrete acoustic signals in the frequency domain and also converts the predicted late reverberations to predicted late reverberations in the frequency domain. A late reverberation eliminator calculates relative values between the amplitude spectra of the discrete acoustic signals expressed in the frequency domain and the amplitude spectra of the predicted late reverberations expressed in the frequency domain, and provides the relative values as predicted amplitude spectra of a dereverberation signal.

Abstract: According to one embodiment, an apparatus for discriminating speech/non-speech of a first acoustic signal includes a weight assignment unit, a feature extraction unit, and a speech/non-speech discrimination unit. The first acoustic signal includes a user's speech and a reproduced sound. The reproduced sound is a system sound having a plurality of channels reproduced from a plurality of speakers. The weight assignment unit is configured to assign a weight to each frequency band based on the system sound. The feature extraction unit is configured to extract a feature from a second acoustic signal based on the weight of each frequency band. The second acoustic signal is the first acoustic signal in which the reproduced sound is suppressed. The speech/non-speech discrimination unit is configured to discriminate speech/non-speech of the first acoustic signal based on the feature.

Abstract: Speech enhancement in a breathing apparatus is provided using a primary sensor mounted near a breathing mask user's mouth, at least one reference sensor mounted near a noise source, and a processor that combines the signals from these sensors to produce an output signal with an enhanced speech component. The reference sensor signal may be filtered and the result may be subtracted from the primary sensor signal to produce the output signal with an enhanced speech component. A method for detecting the exclusive presence of a low air alarm noise may be used to determine when to update the filter. A triple filter adaptive noise cancellation method may provide improved performance through reduction of filter maladaptation. The speech enhancement techniques may be employed as part of a communication system or a speech recognition system.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for enhancing speech recognition accuracy. In one aspect, a method includes receiving geotagged audio signals that correspond to environmental audio recorded by multiple mobile devices in multiple geographic locations, receiving an audio signal that corresponds to an utterance recorded by a particular mobile device, determining a particular geographic location associated with the particular mobile device, generating a noise model for the particular geographic location using a subset of the geotagged audio signals, where noise compensation is performed on the audio signal that corresponds to the utterance using the noise model that has been generated for the particular geographic location.

Abstract: A relay device 20 duplicates speech data received from a communication terminal that is engaged in voice communication with another communication terminal. The duplicated speech data is transmitted to and is stored at a media processing device 40. Media processing device 40 builds a database for speech synthesis based on the stored speech data.

Abstract: A system and method for analyzing a signal to monitor the dynamics of its magnitude and frequency characteristics over time. An electronic circuit for identifying feedback in an audio signal, formed in accordance with embodiments of the invention may comprise a feedback control block operable to determine a candidate frequency having potential feedback such that the feedback control block is further operable to perform an iterative analysis of the magnitude of the audio signal at the candidate frequency to determine the growth characteristics of the signal. The electronic circuit may further include a test filter block operable to deploy a test filter at a candidate frequency and a permanent filter block operable to deploy a permanent filter at the candidate frequency if the feedback control block determines that the growth characteristics of the signal at the candidate frequency comprises feedback characteristics after the test filter has been deployed.

Abstract: An enhancement system improves the estimate of noise from a received signal. The system includes a spectrum monitor that divides a portion of the signal at more than one frequency resolution. Adaptation logic derives a noise adaptation factor of the received signal. A plurality of devices tracks the characteristics of an estimated noise in the received signal and modifies multiple noise adaptation rates. Weighting logic applies the modified noise adaptation rates derived from the signal divided at a first frequency resolution to the signal divided at a second frequency resolution.

Abstract: A communication device includes memory, an input interface, a processing module, and a transmitter. The processing module receives a digital signal from the input interface, wherein the digital signal includes a desired digital signal component and an undesired digital signal component. The processing module identifies one of a plurality of codebooks based on the undesired digital signal component. The processing module then identifies a codebook entry from the one of the plurality of codebooks based on the desired digital signal component to produce a selected codebook entry. The processing module then generates a coded signal based on the selected codebook entry, wherein the coded signal includes a substantially unattenuated representation of the desired digital signal component and an attenuated representation of the undesired digital signal component. The transmitter converts the coded signal into an outbound signal in accordance with a signaling protocol and transmits it.

Abstract: A method, a device and a system for voice encoding/decoding are disclosed in the present invention. The method includes: assembling an input pulse code modulation signal into one signal according to a designated time slot and assembly manner; and encoding the assembled signal according to a designated encoding manner to output an encoded voice signal. In the present invention, because a process of assembling or splitting the signal may be implemented through software, in the case that hardware in a current network does not need to be replaced, an effect of encoding/decoding voice with a 7 K spectrum may be achieved in the current network.

Abstract: Microphone arrays (MAs) are described that position and vent microphones so that performance of a noise suppression system coupled to the microphone array is enhanced. The MA includes at least two physical microphones to receive acoustic signals. The physical microphones make use of a common rear vent (actual or virtual) that samples a common pressure source. The MA includes a physical directional microphone configuration and a virtual directional microphone configuration. By making the input to the rear vents of the microphones (actual or virtual) as similar as possible, the real-world filter to be modeled becomes much simpler to model using an adaptive filter.

Abstract: A noise elimination method and apparatus. The method eliminates noise from an input signal containing a voice signal mixed with a noise signal. The method includes detecting a noise section, in which the noise signal is present, from the input signal; obtaining a weight to be used for the input signal from signals of the noise section; and filtering the input signal using the obtained weight. The method and apparatus enable a mobile robot to eliminate noise in real time and effectively detect and recognize voice.

Abstract: An audio processing apparatus is provided. A beamformer receives input signals and processes the input signals to generate a first processed signal. The input signals include at least one of a source signal and interference. A blocking matrix receives the input signals and operates to cancel the source signal from the input signals to generate a second processed signal. A first adaptive filter has adaptable first filter coefficients, generates a first filtered signal approximating the interference according to the first and second processed signals and continuously adapts the first filter coefficients according to the first filtered signal and the first processed signal. A second adaptive filter has adaptable second filter coefficients, generates a second filtered signal approximating the interference according to the first and second processed signals and selectively adapts the second filter coefficients according to the first filter coefficients and an output signal.

Abstract: A sound signal correcting apparatus converts an acquired sound signal into a phase spectrum and an amplitude spectrum by an FFT process, compares the amplitude spectrum of the obtained sound signal with a noise model so that a correction coefficient used for correcting the amplitude spectrum of the sound signal is derived, smoothes waveform of the amplitude spectrum of the sound signal using the derived correction coefficient, and converts the sound signal into a sound signal where the amplitude spectrum is corrected by performing an inverse FFT process on the phase spectrum and the smoothed amplitude spectrum.

Abstract: A multi-channel audio decoder reconstructs multi-channel audio of more than two physical channels from a reduced set of coded channels based on correlation parameters that specify a full power cross-correlation matrix of the physical channels, or merely preserve a partial correlation matrix (such as power of the physical channels, and some subset of cross-correlations between the physical channels, or cross-correlations of the physical channels with coded or virtual channels).

Abstract: The invention provides a method and device for enhancing the listening qualities of an audio file by providing the listener with a plurality of modified equalized audio files. Each modified equalized audio file having a consistent loudness level but different audio characteristics. Hence, for an input audio file the current invention allows the listener to individually select the best audio characteristics for them to listen to the content of the input audio file according to their particular requirements without them needing to adjust the loudness level in playback. The invention further enables the listener to switch between the multiple equalized audio files during playback. The invention further includes a SN detector and reducer to eliminate the adverse effects of the presence of sudden, strong noise in the input audio file in the process of generating the plurality of modified equalized audio files.

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: An apparatus is shown for detecting speech in an audio signal obtained from an input device, the audio including speech and noise. The apparatus includes a processing circuit which includes a filter configured to smooth the audio signal. The processing circuit is configured to control the bandwidth of the filter based on characteristics of the audio signal and to provide a smoothed signal obtained from the filter to a voice activity detector configured to determine whether the smoothed signal represents speech.

Abstract: In accordance with an example embodiment of the invention, there is provided an apparatus for detecting voice activity in an audio signal. The apparatus comprises a first voice activity detector for making a first voice activity detection decision based at least in part on the voice activity of a first audio signal received from a first microphone. The apparatus also comprises a second voice activity detector for making a second voice activity detection decision based at least in part on an estimate of a direction of the first audio signal and an estimate of a direction of a second audio signal received from a second microphone. The apparatus further comprises a classifier for making a third voice activity detection decision based at least in part on the first and second voice activity detection decisions.

Abstract: A signal bandwidth extension apparatus includes a determination unit which determines whether or not a peak component of the input signal is lacked in the band to be extended, and a control unit which controls to extend the bandwidth when the determination unit determines that the peak component of the input signal is lacked in the band to be extended, and not to extend the bandwidth when the determination unit determines that the peak component is not lacked.

Abstract: A system evaluates a hands free communication system. The system automatically selects a consonant-vowel-consonant (CVC), vowel-consonant-vowel (VCV), or other combination of sounds from an intelligent database. The selection is transmitted with another communication stream that temporally overlaps the selection. The quality of the communication system is evaluated through an automatic speech recognition engine. The evaluation occurs at a location remote from the transmitted selection.

Abstract: In one embodiment, a highband burst suppressor includes a first burst detector configured to detect bursts in a lowband speech signal, and a second burst detector configured to detect bursts in a corresponding highband speech signal. The lowband and highband speech signals may be different (possibly overlapping) frequency regions of a wideband speech signal. The highband burst suppressor also includes an attenuation control signal calculator configured to calculate an attenuation control signal according to a difference between outputs of the first and second burst detectors. A gain control element is configured to apply the attenuation control signal to the highband speech signal. In one example, the attenuation control signal indicates an attenuation when a burst is found in the highband speech signal but is absent from a corresponding region in time of the lowband speech signal.

Abstract: A method is provided for multi-pass echo residue detection. The method includes detecting audio data, and determining whether the audio data is recognized as speech. Additionally, the method categorizes the audio data recognized as speech as including an acceptable level of residual echo, and categorizes categorizing unrecognizable audio data as including an unacceptable level of residual echo. Furthermore, the method determines whether the unrecognizable audio data contains a user input, and also determines whether a duration of the user input is at least a predetermined duration, and when the user input is at least the predetermined duration, the method extracts the predetermined duration of the user input from a total duration of the user input.

Abstract: Methods, systems, and computer program products are provided for generating and posting messages to social networks based on voice input. One example method includes receiving an audio signal that corresponds to spoken content, generating one or more representations of the spoken content, and causing the one or more representations of the spoken content to be posted to a social network.

Abstract: An architecture and framework for speech/noise classification of an audio signal using multiple features with multiple input channels (e.g., microphones) are provided. The architecture may be implemented with noise suppression in a multi-channel environment where noise suppression is based on an estimation of the noise spectrum. The noise spectrum is estimated using a model that classifies each time/frame and frequency component of a signal as speech or noise by applying a speech/noise probability function. The speech/noise probability function estimates a speech/noise probability for each frequency and time bin. A speech/noise classification estimate is obtained by fusing (e.g., combining) data across different input channels using a layered network model.

Abstract: A speech recognition system includes a receiver component that receives a distorted speech utterance. The speech recognition also includes an adaptor component that selectively adapts parameters of a compressed model used to recognize at least a portion of the distorted speech utterance, wherein the adaptor component selectively adapts the parameters of the compressed model based at least in part upon the received distorted speech utterance.

Abstract: An architecture and framework for speech/noise classification of an audio signal using multiple features with multiple input channels (e.g., microphones) are provided. The architecture may be implemented with noise suppression in a multi-channel environment where noise suppression is based on an estimation of the noise spectrum. The noise spectrum is estimated using a model that classifies each time/frame and frequency component of a signal as speech or noise by applying a speech/noise probability function. The speech/noise probability function estimates a speech/noise probability for each frequency and time bin. A speech/noise classification estimate is obtained by fusing (e.g., combining) data across different input channels using a layered network model.

Abstract: Embodiments of the invention disclose computer-implemented methods, systems, and computer program products for estimating signal coherence. First, a sound generated by a sound source is detected by a first microphone to obtain a first microphone signal and by a second microphone to obtain a second microphone signal. The first microphone signal is filtered by a first adaptive finite impulse response filter to obtain a first filtered signal. The second microphone signal is filtered by a second adaptive finite impulse response filter, to obtain a second filtered signal. The coherence of the first filtered signal and the second filtered signal is determined based upon the filtered signals.