Abstract: An apparatus comprising a first antenna array and a second antenna array, each antenna array comprising a set of antennas, wherein for both antenna arrays, the positions of each two adjacent antennas are different in relation to a first axis and in relation to a second axis, perpendicular to the first axis.

Abstract: An apparatus comprising a first antenna array and a second antenna array, each antenna array comprising a set of antennas, wherein for both antenna arrays, the positions of each two adjacent antennas are different in relation to a first axis and in relation to a second axis, perpendicular to the first axis.

Abstract: Device, system, and method of source separation, Blind Source Separation (BSS), signal processing, enhancement of acoustic signals, and reduction of noise from acoustic signals. A first acoustic microphone captures a first acoustic signal at a first location. A second acoustic microphone captures a second acoustic signal at a second location. An optical microphone or laser microphone, that targets or aims towards the first location and not towards the second location, captures an optical feedback signal. One or more correlator units, and one or more de-correlator units, perform particular correlation operations and de-correlation operations, among the first acoustic signal, the second acoustic signal, and the optical feedback signal; and produce, separately, a cleaned or reduced-noise version of the first acoustic signal, as well as a cleaned or reduced-noise version of the second acoustic signal.

Abstract: Devices, systems, and methods of enhanced automatic speech recognition. An acoustic microphone senses or captures acoustic signals that are uttered by a human speaker. An optical microphone or laser microphone transmits a laser beam aimed towards the face of the human speaker; receives a reflected optical feedback signal; and produces an optical self-mix signal by self-mixing interferometry. The self-mix signal is used by a training unit of a speech recognition processor. Optionally, the self-mix signal is used by an utterance recognition unit of the speech recognition processor. Optionally, the self-mix signal is utilized for enhancing the acoustic signals, or for constructing a digital filter that is applied to the acoustic signal; and the enhanced acoustic signal, or the filtered acoustic signal, is used by the training unit or by the a recognition unit of the speech recognition processor.

Abstract: System, device, and method of sound isolation and signal enhancement. A hybrid device, or hybrid microphone, or a directional hybrid acoustic-and-optical microphone device, includes: a laser microphone to transmit a laser beam towards a sound-source, and to receive optical feedback reflected from a vibrating surface of the sound-source; an acoustic microphone to capture an acoustic signal which includes (i) sounds produced by the sound-source, and (ii) other concurrent sounds produced externally to the sound-source; a processing unit (a) to process the received optical feedback, and (b) to dynamically enhance the acoustic signal based on the received optical feedback. The processing unit includes or utilizes a digital filter constructor module to dynamically construct, based on the received optical feedback and based on the acoustic signals captured by the acoustic microphone, a digital filter to filter the other concurrent noises from the acoustic signal.

Abstract: A system for distinguishing and identifying speech segments originating from speech of one or more relevant speakers in a predefined detection area. The system includes an optical system which outputs optical patterns, each representing audio signals as detected by the optical system in the area within a specific time frame; and a computer processor which receives each of the outputted optical patterns and analyses each respective optical pattern to provide information that enables identification of speech segments thereby, by identifying blank spaces in the optical pattern, which define beginning or ending of each respective speech segment.

Abstract: System and method for producing enhanced speech data associated with at least one speaker. The process of producing the enhanced speech data comprises: receiving distant signal data from a distant acoustic sensor; receiving proximate signal data from a proximate acoustic sensor located closer to the speaker than the distant acoustic sensor; receiving optical data originating from an optical unit configured for optically detecting acoustic signals in an area of the speaker and outputting data associated with speech of the speaker; processing the distant and proximate signals data for producing a speech reference and a noise reference; operating an adaptive noise estimation module, which identifies stationary and/or transient noise signal components, using the noise reference; and operating a post filtering module, which uses the optical data, speech reference and identified noise signal components for creating an enhanced speech data.

Abstract: Method and system for tracking fundamental frequencies of pseudo-periodic signals in the presence of noise that include receiving a time-frequency representation of signals measured in a predefined environment; estimating and tracking a fundamental frequency of a respective pseudo-periodic signal at each time frame of the time-frequency representation by tracking detections of harmonious frequencies in the time-frequency representation over time; and outputting each respective estimated fundamental frequency associated with the pseudo-periodic signal of each respective time frame.

Abstract: A system for distinguishing and identifying speech segments originating from speech of one or more relevant speakers in a predefined detection area. The system includes an optical system which outputs optical patterns, each representing audio signals as detected by the optical system in the area within a specific time frame; and a computer processor which receives each of the outputted optical patterns and analyses each respective optical pattern to provide information that enables identification of speech segments thereby, by identifying blank spaces in the optical pattern, which define beginning or ending of each respective speech segment.

Abstract: Method and system for tracking fundamental frequencies of pseudo-periodic signals in the presence of noise that include receiving a time-frequency representation of signals measured in a predefined environment; estimating and tracking a fundamental frequency of a respective pseudo-periodic signal at each time frame of the time-frequency representation by tracking detections of harmonious frequencies in the time-frequency representation over time; and outputting each respective estimated fundamental frequency associated with the pseudo-periodic signal of each respective time frame.