Abstract: A virtual assistant uses context information to supplement natural language or gestural input from a user. Context helps to clarify the user's intent and to reduce the number of candidate interpretations of the user's input, and reduces the need for the user to provide excessive clarification input. Context can include any available information that is usable by the assistant to supplement explicit user input to constrain an information-processing problem and/or to personalize results. Context can be used to constrain solutions during various phases of processing, including, for example, speech recognition, natural language processing, task flow processing, and dialog generation.

Abstract: An audio spatial rendering apparatus and method are disclosed. In one embodiment, The audio spatial rendering apparatus includes a rendering unit for spatially rendering an audio stream so that the reproduced far-end sound is perceived by a listener as originating from at least one virtual spatial position, a real position obtaining unit for obtaining a real spatial position of a real sound source, a comparator for comparing the real spatial position with the at least one virtual spatial position; and an adjusting unit for, where the real spatial position is within a predetermined range around at least one virtual spatial position, or vice versa, adjusting the parameters of the rendering unit so that the at least one virtual spatial position is changed.

Abstract: A system includes a speech recognition processor, a depth sensor coupled to the speech recognition processor, and an array of microphones coupled to the speech recognition processor. The depth sensor is operable to calculate a distance and a direction from the array of microphones to a source of audio data. The speech recognition processor is operable to select an acoustic model as a function of the distance and the direction from the array of microphones to the source of audio data. The speech recognition processor is operable to apply the distance measure in the microphone array beam formation so as to boost portions of the signals originating from the source of audio data and to suppress portions of the signals resulting from noise.

Abstract: A system and method for data storage by shredding and deshredding of the data allows for various combinations of processing of the data to provide various resultant storage of the data. Data storage and retrieval functions include various combinations of data redundancy generation, data compression and decompression, data encryption and decryption, and data integrity by signature generation and verification. Data shredding is performed by shredders and data deshredding is performed by deshredders that have some implementations that allocate processing internally in the shredder and deshredder either in parallel to multiple processors or sequentially to a single processor. Other implementations use multiple processing through multi-level shredders and deshredders. Redundancy generation includes implementations using non-systematic encoding, systematic encoding, or a hybrid combination.

Abstract: To input the voice of the passenger of a vehicle and output a piece of high-quality enhanced speech independently of the direction of a piece of speech or noise, a speech processing apparatus includes a first microphone that is provided on one of a ceiling member in a vehicle and an accessory thereof, inputs a sound mixture including a voice of a passenger of the vehicle and noise in the vehicle, and outputs a first signal, a second microphone that is provided on one of the ceiling member in the vehicle and the accessory thereof at a position farther than the first microphone when viewed from the passenger of the vehicle, inputs the noise in the vehicle while insulating the voice of the passenger of the vehicle using one of the ceiling member of the vehicle and the accessory thereof, and outputs a second signal, and a noise suppressor that outputs an enhanced speech signal based on the first signal and the second signal.

Abstract: Provided are a noise floor level reduction device and a noise floor level reduction method capable of reducing a noise floor level. A transmission power measurement system 10 is installed before a signal measurement device 20 including a noise floor level measurement unit 22 that measures a noise floor level, and a measurement unit 24 that subtracts the noise floor level from a level of a signal from a DUT 2 to calculate a level of a signal after subtraction, and includes an LNA 17 provided between the DUT 2 and the signal measurement device 20 for amplifying the signal from the DUT 2, and a termination resistor 16 that terminates an input of the LNA 17, and the termination resistor 16 terminates the input of the LNA 17 in a case in which the noise floor level measurement unit 22 measures the noise floor level.

Abstract: A receiving device having a wireless transmission circuit arranged to form a logical communications link between the wireless transmission circuit and an audio output device. The wireless transmission circuit is arranged to communicate audio data to the audio output device via the logical communications link. A wireless reception circuit is arranged to receive user commands, and a first logic circuit is arranged to identify a mute command received via the wireless reception circuit. A second logic circuit is arranged to mute the audio data from transmission to the audio output device while maintaining the logical communications link.

Abstract: According to one aspect, a method for detecting voice activity is disclosed, the method including receiving a frame of an input audio signal, the input audio signal having an sample rate; dividing the frame into a plurality of subbands based on the sample rate, the plurality of subbands including at least a lowest subband and a highest subband; filtering the lowest subband with a moving average filter to reduce an energy of the lowest subband; estimating a noise level for each of the plurality of subbands; calculating a signal to noise ratio value for each of the plurality of subbands; and determining a speech activity level of the frame based on an average of the calculated signal to noise ratio values and a weighted average of an energy of each of the plurality of subbands. Other aspects include audio decoders that decode audio that was encoded using the methods described herein.

Abstract: An echo cancellation system that generates multiple output paths, enabling Automatic Speech Recognition (ASR) processing in parallel with voice communication. For single direction AEC (e.g., ASR processing), the system prioritizes speech from a single user and ignores other speech by selecting a single directional output from a plurality of directional outputs as a first output path. For multi-directional AEC (e.g., voice communication), the system includes all speech by combining the plurality of directional outputs as a second output path. The system may use a weighted sum technique, such that each directional output is represented in the combined output based on a corresponding signal metric, or an equal weighting technique, such that a first group of directional outputs having a higher signal metric may be equally weighted using a first weight while a second group of directional outputs having a lower signal metric may be equally weighted using a second weight.

Abstract: A hands-free audio device has a receive path and a transmit path, which may operate at different audio sampling rates. The transmit path has an interference suppressor that receives a reference signal from the receive path and that suppresses interference in microphone signals received from a microphone array. The interference suppressor is followed in the transmit path by a multi-channel adaptive beamformer that produce a plurality of directional audio signals. A beam selector is configured to select one of the directional audio signals based on voice activity, echo detection, and signal energy.

Abstract: Provided is an apparatus for large vocabulary continuous speech recognition (LVCSR) based on a context-dependent deep neural network hidden Markov model (CD-DNN-HMM) algorithm. The apparatus may include an extractor configured to extract acoustic model-state level information corresponding to an input speech signal from a training data model set using at least one of a first feature vector based on a gammatone filterbank signal analysis algorithm and a second feature vector based on a bottleneck algorithm, and a speech recognizer configured to provide a result of recognizing the input speech signal based on the extracted acoustic model-state level information.

Abstract: Disclosed are systems, methods, and computer readable media for identifying an acoustic environment of a caller. The method embodiment comprises analyzing acoustic features of a received audio signal from a caller, receiving meta-data information based on a previously recorded time and speed of the caller, classifying a background environment of the caller based on the analyzed acoustic features and the meta-data, selecting an acoustic model matched to the classified background environment from a plurality of acoustic models, and performing speech recognition as the received audio signal using the selected acoustic model.

Abstract: The purpose of the present invention is to achieve a high-quality signal processing performance. A signal processing device provided with a suppression unit for suppressing a second signal by processing a mixed signal in which a first signal and the second signal are present. The signal processing device is provided with an analysis unit for analyzing, per frequency component, the importance of the first signal contained in the mixed signal, and an inhibition unit for inhibiting the suppression of the second signal of a frequency component having a high importance over a frequency component having a low importance on the basis of the analysis result of the analysis means.

Abstract: The embodiments of the present invention relates to a voice activity detector and a method thereof. The voice activity detector is configured to detect voice activity in a received input signal comprising an input section configured to receive a signal from a primary voice detector of said VAD indicative of a primary VAD decision and at least one signal from at least one external VAD indicative of a voice activity decision from the at least one external VAD, a processor configured to combine the voice activity decisions indicated in the received signals to generate a modified primary VAD decision, and an output section configured to send the modified primary VAD decision to a hangover addition unit of said VAD.

Abstract: A method and system for distributed text-to-speech synthesis and intelligibility, and more particularly to distributed text-to-speech synthesis on handheld portable computing devices that can be used for example to generate intelligible audio prompts that help a user interact with a user interface of the handheld portable computing device. The text-to-speech distributed system 70 receives a text string from the guest devices and comprises a text analyzer 72, a prosody analyzer 74, a database 14 that the text analyzer and prosody analyzer refer to, and a speech synthesizer 80. Elements of the speech synthesizer 80 are resident on the host device and the guest device and an audio index representation of the audio file associated with the text string is produced at the host device and transmitted to the guest device for producing the audio file at the guest device.

Abstract: The disclosure provides a method and an apparatus for detecting a voice activity in an input audio signal composed of frames. A noise attribute of the input signal is determined based on a received frame of the input audio signal. A voice activity detection (VAD) parameter is derived based on the noise attribute of the input audio signal using an adaptive function. The derived VAD parameter is compared with a threshold value to provide a voice activity detection decision. The input audio signal is processed according to the voice activity detection decision.

Abstract: An acoustic-scene interpretation apparatus can have a transducer configured to convert an acoustic signal to a corresponding electrical signal. A feature extractor can receive a sequence of frames representing the electrical signal and extract a plurality of acoustic features corresponding to each frame. An acoustic-scene classifier can be configured to determine a most-likely acoustic state for each frame in the sequence of frames in correspondence with the respective plurality of acoustic features corresponding to the frame and a selected probability distribution of duration of an acoustic state for each of one or more classes of acoustic scenes. Each respective probability distribution of duration can correspond to a selected class of acoustic scenes. The correspondence between acoustic state and probability distribution of duration can be learned from training data corresponding to each of a plurality of classes of acoustic scenes. Related methods also are disclosed.

Abstract: A sound signal processing method, the sound signal processing apparatus and the vehicle equipped with the apparatus, in which the sound signal processing apparatus includes a spatial filtering unit configured to obtain a filtered signal including a target signal by a spatial filtering by applying a spatial filter to an input signal, and a mask application unit configured to obtain an output signal by applying a mask to the filtered signal. The mask may be obtained by using a spatial selectivity between the target signal and noise of the target signal.

Abstract: Devices, systems and methods are disclosed for reducing noise in input data by performing a hysteresis operation followed by a lateral excitation smoothing operation. For example, an audio signal may be represented as a sequence of feature vectors. A row of the sequence of feature vectors may, for example, be associated with the same harmonic of the audio signal at different points in time. To determine portions of the row that correspond to the harmonic being present, the system may compare an amplitude to a low threshold and a high threshold and select a series of data points that are above the low threshold and include at least one data point above the high threshold. The system may iteratively perform a spreading technique, spreading a center value of a center data point in a kernel to neighboring data points in the kernel, to further reduce noise.

Abstract: An apparatus comprising: a detector configured to determine at least one microphone is impaired by analyzing at least one audio signal from the at least one microphone; and an controller configured to determine an indicator based on the determination of the impairment of the at least one microphone; and configured to apply the indicator based on the determination of the impairment of the at least one microphone, such that the at least one audio signal is processed based on the indicator.

Abstract: Features are disclosed for detecting words in audio using environmental information and/or contextual information in addition to acoustic features associated with the words to be detected. A detection model can be generated and used to determine whether a particular word, such as a keyword or “wake word,” has been uttered. The detection model can operate on features derived from an audio signal, contextual information associated with generation of the audio signal, and the like. In some embodiments, the detection model can be customized for particular users or groups of users based usage patterns associated with the users.

Abstract: A method for analysis of a set of media recordings includes, in a first processing stage, selecting a subset of the set of media recordings by performing a first processing of each media recording of the set of media recordings and in a second processing stage, performing a second processing of the subset of the set of media recordings, the second processing including extraction of information from the media recordings of the subset of the set of media recordings. The first processing of each media recording of the set of media recordings includes determining a characterization of the media recording, the characterization including at least a quantity characterizing a predicted performance of the second processing of the media recording.

Abstract: The systems, devices, and processes described herein may include a first microphone that detects a target voice of a user within an environment and a second microphone that detects other noise within the environment. A target voice estimate and/or a noise estimate may be generated based at least in part on one or more adaptive filters. Based at least in part on the voice estimate and/or the noise estimate, an enhanced target voice and an enhanced interference, respectively, may be determined. One or more words that correspond to the target voice may be determined based at least in part on the enhanced target voice and/or the enhanced interference. In some instances, the one or more words may be determined by suppressing or canceling the detected noise.

Abstract: Systems and techniques for adding pitch shift resistance to an audio fingerprint are presented. In particular, an audio track for a media file is received. A first audio fingerprint for the audio track with a first pitch shift and an Nth audio fingerprint for the audio track with an Mth pitch shift are generated, where N is an integer greater than or equal to two and M is an integer greater than or equal to two. A combined audio fingerprint is generated from at least the first audio fingerprint and the Nth audio fingerprint.

Abstract: A mobile device is adapted for automatic speech recognition (ASR). A user interface for interaction with a user includes an input microphone for obtaining speech inputs from the user for automatic speech recognition, and an output interface for system output to the user based on ASR results that correspond to the speech input. A local controller obtains a sample of non-ASR audio from the input microphone for ASR-adaptation to channel-specific ASR characteristics, and then provides a representation of the non-ASR audio to a remote ASR server for server-side adaptation to the channel-specific ASR characteristics, and then provides a representation of an unknown ASR speech input from the input microphone to the remote ASR server for determining ASR results corresponding to the unknown ASR speech input, and then provides the system output to the output interface.

Abstract: According to some embodiments, a sensor network may be provided with re-programmable and/or reconfigurable analog circuitry configured to monitor data collected by the sensor network. The re-programmable and/or reconfigurable analog circuitry may also generate a wakeup signal in response to a defined wakeup event detected by the sensor network.

Abstract: A communication system includes a headset including a microphone and an audio speaker installed on the headset, the headset including an RF transceiver configured to perform wireless communication with a two-way radio having a push-to-talk communication channel. The RF transceiver is further configured to perform wireless communication with an information handling system. The headset includes processing electronics configured to process an input signal from the microphone and output a first processed signal to the RF transceiver and to process an input signal from the RF transceiver and output a second processed signal to the speaker. A remote control unit is configured to perform wireless communication with the headset, the remote control unit including a remote control unit interface disposed thereon for selectively configuring the headset to function as an audio interface for the push-to-talk communication channel and an audio interface for the information handling system.

Abstract: A cloud service system may activate features or functionality based on agreement of at least two parties such as a system administrator and a compliance officer to mitigate compliance, security, or privacy impact on the service. The controllers may make the “enable feature” decision independently, but still have equal say in the outcome. In some examples, pre-established profiles may be provided to a controller such as a compliance officer to make decisions by selection on his/her behalf at a particular level of risk acceptance and/or to meet a particular regulatory standard/certification.

Abstract: Systems and methods for speech recognition system having a speech processor that is trained to recognize speech by considering (1) a raw microphone signal that includes an echo signal and (2) different types of echo information signals from an echo cancellation system (and optionally different types of ambient noise suppression signals from a noise suppressor). The different types of echo information signals may include those used for echo cancelation and those having echo information. The speech recognition system may convert the raw microphone signal and different types of echo information signals (and optional noise suppression signals) into spectral features in the form of a vector, and a concatenator to combine the feature vectors into a total vector (for a period of time) that is used to train the speech processor, and during use of the speech processor to recognize speech.

Abstract: A speech processing device includes a processor; and a memory which stores a plurality of instructions, which when executed by the processor, cause the processor to execute: obtaining input speech, detecting a vowel segment contained in the input speech, estimating an accent segment contained in the input speech, calculating a first vowel segment length containing the accent segment and a second vowel segment length excluding the accent segment, and controlling at least one of the first vowel segment length and the second vowel segment length.

Abstract: A speech-based audio device may be configured to detect a user-uttered trigger expression and to respond by interpreting subsequent words or phrases as commands. In order to distinguish between utterance of the trigger expression by the user and generation of the trigger expression by the device itself, output signals used as speaker inputs are analyzed to detect whether the trigger expression has been generated by the speaker. If a detected trigger expression has been generated by the speaker, it is disqualified. Disqualified trigger expressions are not acted upon the by the audio device.

Abstract: Embodiments of the present invention provide a voice identification method, which includes: obtaining voice data; obtaining a confidence value according to the voice data; obtaining a noise scenario according to the voice data; obtaining a confidence threshold corresponding to the noise scenario; and if the confidence value is greater than or equal to the confidence threshold, processing the voice data. An apparatus is also provided. The method and apparatus that flexibly adjust the confidence threshold according to the noise scenario greatly improve a voice identification rate under a noise environment.

Abstract: A method of operating electric brakes for a vehicle including monitoring at least a voltage in a power system of the vehicle, and adjusting a power provided to the electric brakes based on at least the monitored voltage to control a current according to a predetermined behavior.

Abstract: A sound collecting control apparatus includes: a vehicle stop detector; a noise source direction specifier to specify a direction from the sound collector to a noise source of the vehicle stopped at the predetermined position; a search beam former that forms a plurality of search beams in the direction of the noise source specified by the noise source direction specifier and around the direction of the noise source so as to search for a sound source of a voice of a speaker in the vehicle; a search beam selector that selects a search beam corresponding to the sound source of the voice of the speaker in the vehicle from the plurality of search beams formed by the search beam former; and a directivity former that forms directivity of the sound collected by the sound collector in the direction corresponding to the search beam selected by the search beam selector.

Abstract: Described are noise suppression techniques applicable to various systems including automatic speech processing systems in digital audio pre-processing. The noise suppression techniques utilize a machine-learning framework trained on cues pertaining to reference clean and noisy speech signals, and a corresponding synthetic noisy speech signal combining the clean and noisy speech signals. The machine-learning technique is further used to process audio signals in real time by extracting and analyzing cues pertaining to noisy speech to dynamically generate an appropriate gain mask, which may eliminate the noise components from the input audio signal. The audio signal pre-processed in such a manner may be applied to an automatic speech processing engine for corresponding interpretation or processing.

Abstract: A portable music device may operate in response to user speech. In situations in which the music device is operating primarily from battery power, a push-to-talk (PTT) button may be used to indicate when the user is directing speech to the device. When the music device is receiving external power, the music device may continuously monitor a microphone signal to detect a user utterance of a wakeword, which may be used to indicate that subsequent speech is directed to the device. When operating from battery power, the device may send audio to a network-based support service for speech recognition and natural language understanding. When operating from external power, the speech recognition and/or natural language understanding may be performed by the music device itself.

Abstract: Methods, systems, and techniques of digital signal processing using acoustic arrays are provided. Example embodiments described herein provide enhanced acoustic arrays that utilize MEMS digital microphones to offer greater control and measurement capabilities to users and systems that desire to measure sound typically to derive other data. Large numbers of digital microphones can be manufactured to be placed on an acoustic array to derive a plurality of derived acoustic array measurements.

Abstract: Technology to provide is disclosed. In an example, a user equipment (UE) can include computer circuitry configured to: receive a manifest file for an HTTP adaptive stream from a node; identify an energy characterization in the manifest file for a plurality of representations for a selected period; select a representation for the selected period having a desired energy characterization; and request segments from the node that are in the representation having the desired energy characterization.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech endpointing based on word comparisons are described. In one aspect, a method includes the actions of obtaining a transcription of an utterance. The actions further include determining, as a first value, a quantity of text samples in a collection of text samples that (i) include terms that match the transcription, and (ii) do not include any additional terms. The actions further include determining, as a second value, a quantity of text samples in the collection of text samples that (i) include terms that match the transcription, and (ii) include one or more additional terms. The actions further include classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value.

Abstract: Embodiments of the present invention provide a voice identification method, including: obtaining voice data; obtaining a first confidence value according to the voice data; obtaining a noise scenario according to the voice data; obtaining a second confidence value corresponding to the noise scenario according to the first confidence value; and if the second confidence value is greater than or equal to a pre-stored confidence threshold, processing the voice data. An apparatus is also provided. The method and apparatus that flexibly adjust the confidence value according to the noise scenario greatly improve a voice identification rate under a noise environment.

Abstract: The systems, devices, and processes described herein may generate a signal, such as an audio signal or an electrical signal, that may include echo and/or noise. The echo may be at least partially canceled based at least in part on acoustic echo cancellation or local echo cancellation, while the noise may be at least partially reduced based at least in part on noise reduction. A residual amount of echo and/or noise may then be determined. The residual echo and/or noise may be suppressed based at least in part on adaptive filtering of the signal, which may include modifying weights of an algorithm associated with an adaptive filter.

Abstract: The present invention provides a system and method for generating a dataset of uncompressed color images taken with three digital cameras and exhibiting different levels of real noise, resulting from low-light conditions. For each scene there are, on average, two low-noise and two noisy images that are aligned at the pixel level both spatially and in intensity. In one embodiment, the dataset contains over 100 scenes and more than 400 images, including both 16-bit RAW formatted images and 8-bit BMP pixel and intensity aligned images from three digital cameras. The generated dataset of real noise images is useful in the evaluation of denoising algorithms.

Abstract: In accordance with an embodiment of the present invention, a noise reduction method for speech processing includes estimating a noise/interference component signal by subtracting voice component signal from a first microphone input signal wherein the voice component signal is evaluated as a first replica signal produced by passing a second microphone input signal through a first adaptive filter; a stepsize is estimated to control adaptive update of the first adaptive filter, wherein the stepsize is evaluated by combing an open-loop approach and a closed-loop approach, the open-loop approach comprising voice/noise/interference classification and SNR estimation in voice area, and the closed-loop approach comprising calculating a normalized correlation between the first replica signal and the first microphone input signal.

Abstract: A sound source separating device includes: a sound collecting unit configured to collect sound signals using a plurality of microphones; a sound source localizing unit configured to localize a sound source on the basis of the sound signals collected by the sound collecting unit; a sound source separating unit configured to separate the sound signals collected by the sound collecting unit into sound sources corresponding to the number of fixed sound sources and fixed sound source directions without using the sound source localization result from the sound source localizing unit; and a speech extracting unit configured to extract speech signals of the fixed sound sources on the basis of the sound source localization result from the sound source localizing unit and the sound source separation result from the sound source separating unit.

Abstract: Methods, systems, computer-readable media, and apparatuses for inferring context are provided. In one potential implementation, first context information associated with a first duration is identified, second context information is accessed to determine a context segmentation boundary; and the first context information and the second context information is then aggregated to generate an inferred segmented aggregated context. In a further implementation, the first context information is used to average inferred contexts, and the context segmentation boundary is used to reset a start time for averaging the first context information.

Abstract: The present invention provides a system and method encompassing a new metric and MATLAB tool box that phone makers may use to improve the design of the secondary path, in order to improve ANC performance. The metric measures how invertible the secondary path is and then evaluates ANC performance at a worst case scenario where P(z)=1 and W(z) becomes a complete predictor. The invention can be easily extended to a multi-channel ANC system.

Abstract: A close-talk detector detects a near-end user's speech signal, while an adaptive ANC process is running, and in response helps prevent the filter coefficients of an adaptive filter of the ANC process from being corrupted, thereby reducing the risk of the adaptive filters diverge. Upon detecting speech using a vibration sensor signal and one or more microphone signals, the detector asserts a signal that slows down, or even freezes or halts, the adaptation of the adaptive filter. The signal may be de-asserted when no more speech is being detected, thereby allowing the adaptive ANC process to resume its normal rate adaptation of the filter. The detector may continuously operate in this manner during the call, as the user talks and then pauses and then resumes talking. Other embodiments are also described.

Abstract: Examples disclose a low power integrated circuit to receive and digitize an audio stream. Further, the examples provide the low power integrated circuit to compare the digitized audio stream to a keyword and store the digitized audio stream in a memory. Additionally, the examples also disclose upon recognition of the keyword in the digitized audio stream, the low power integrated circuit transmits a signal to a processor to increase power and analyze the digitized audio stream.

Abstract: A system for processing audio data comprising a linear demixing system configured to receive a plurality of sub-band audio channels and to generate an audio output and a noise output. A spatial likelihood system coupled to the linear demixing system, the spatial likelihood system configured to receive the audio output and the noise output and to generate a spatial likelihood function. A sequential Gaussian mixture model system coupled to the spatial likelihood system, the sequential Gaussian mixture model system configured to generate a plurality of model parameters. A Bayesian probability estimator system configured to receive the plurality of model parameters and a speech/noise presence probability and to generate a noise power spectral density and spectral gains. A spectral filtering system configured to receive the spectral gains and to apply the spectral gains to noisy input mixtures.

Abstract: A processor-implemented method for spatial sound localization and isolation is described. The method includes segmenting, via a processor, each of a plurality of source signals detected by a plurality of sensors, into a plurality of time frames. For each time frame, the method further includes obtaining, via a processor, a plurality of direction of arrival (DOA) estimates from the plurality of sensors, discretizing an area of interest into a plurality of grid points, calculating, via the processor, DOA at each of grid points, comparing, via the processor, the DOA estimates with the computed DOAs. If the number of sources is more than 1, the method includes obtaining via the processor, a plurality of combinations of DOA estimates, from amongst the plurality of combinations, estimating, via the processor, one or more initial candidate locations corresponding to each of the combinations, selecting location of the sources from amongst the initial candidate locations.