Abstract: Processing sound signals acquired by at least one microphone, to locate a sound source emitting from a plurality of discrete positions at respective discrete points in time, in a space comprising at least one planar reflective surface. The method includes: obtaining: a first vector u ? 0 ( k ) determining a direction of a first acoustic path, direct between the source and the microphone, a second vector u ? n ( k ) representing a second acoustic path resulting from a specular reflection and arriving at the microphone, and a delay ? n ( k ) of second path at the microphone, compared to the direct path; exploiting a property of the specular reflection according to which a Euclidean distance between two positions of the source at two discrete points in time is equal to a Euclidean distance between two respective positions of images of the source and derived from one or more same reflections, respectively at said two discrete points in time.

Abstract: A method of processing audio signals acquired by at least one microphone to locate a sound source in a space having a wall. The method includes applying a time-frequency transform to the acquired signals and expressing a general complex velocity vector with a real part and an imaginary part in the frequency domain. The vector has a denominator with a component other than an omnidirectional component and characterizes a composition between: a first acoustic path, direct between the source and the microphone, represented by a first vector, and a second acoustic path resulting from a reflection on the wall and represented by a second vector. The second path has a delay relative to the direct path. A direction of the direct path, a distance from the source to the microphone, and/or a distance from the source to the wall is determined as a function of the delay and the vectors.

Abstract: Processing sound signals acquired by at least one microphone, to locate a sound source emitting from a plurality of discrete positions at respective discrete points in time, in a space comprising at least one planar reflective surface. The method includes: obtaining: a first vector {right arrow over (u)}0(k) determining a direction of a first acoustic path, direct between the source and the microphone, a second vector {right arrow over (u)}n(k) representing a second acoustic path resulting from a specular reflection and arriving at the microphone, and a delay ?n(k) of second path at the microphone, compared to the direct path; exploiting a property of the specular reflection according to which a Euclidean distance between two positions of the source at two discrete points in time is equal to a Euclidean distance between two respective positions of images of the source and derived from one or more same reflections, respectively at said two discrete points in time.

Abstract: Processing sound signals acquired by a microphone, for example an ambisonic type, to locate a sound source in a space including at least one wall. A time-frequency transform is applied to the acquired signals, and, from the acquired signals, a velocity vector, complex with real and imaginary parts, is expressed in the frequency domain, wherein the velocity vector characterizes a composition between: a first acoustic path, direct between the source and the microphone, represented by a first vector; and a second acoustic path resulting from a reflection on the wall and represented by a second vector. The second path has a first delay with respect to the direct path. Depending on the first delay and the first and second vectors, a parameter is determined from among a direction of the direct path, a distance from the source to the microphone, and a distance from the source to said wall.

Abstract: A method of processing audio signals acquired by at least one microphone to locate a sound source in a space having a wall. The method includes applying a time-frequency transform to the acquired signals and expressing a general complex velocity vector with a real part and an imaginary part in the frequency domain. The vector has a denominator with a component other than an omnidirectional component and characterizes a composition between: a first acoustic path, direct between the source and the microphone, represented by a first vector, and a second acoustic path resulting from a reflection on the wall and represented by a second vector. The second path has a delay relative to the direct path. A direction of the direct path, a distance from the source to the microphone, and/or a distance from the source to the wall is determined as a function of the delay and the vectors.

Abstract: Processing acoustic signals to detect sound sources in a sound scene. The method includes: obtaining a plurality of signals representative of the sound scene, captured by a plurality of microphones of predefined positions; based on the signals captured by the microphones and on the positions of the microphones, applying a quantization of directional measurements of sound intensity and establishing a corresponding acoustic activity map in a sound source localization space, the space being of dimension N; constructing at least one vector basis of dimension less than N; projecting the acoustic activity map onto at least one axis of the vector basis; and searching for at least one local peak of acoustic activity in the map projection, an identified local peak corresponding to the presence of a sound source in the scene.

Abstract: Processing sound signals acquired by a microphone, for example an ambisonic type, to locate a sound source in a space including at least one wall. A time-frequency transform is applied to the acquired signals, and, from the acquired signals, a velocity vector, complex with real and imaginary parts, is expressed in the frequency domain, wherein the velocity vector characterizes a composition between: a first acoustic path, direct between the source and the microphone, represented by a first vector; and a second acoustic path resulting from a reflection on the wall and represented by a second vector. The second path has a first delay with respect to the direct path. Depending on the first delay and the first and second vectors, a parameter is determined from among a direction of the direct path, a distance from the source to the microphone, and a distance from the source to said wall.

Abstract: Processing acoustic signals to detect sound sources in a sound scene. The method includes: obtaining a plurality of signals representative of the sound scene, captured by a plurality of microphones of predefined positions; based on the signals captured by the microphones and on the positions of the microphones, applying a quantization of directional measurements of sound intensity and establishing a corresponding acoustic activity map in a sound source localization space, the space being of dimension N; constructing at least one vector basis of dimension less than N; projecting the acoustic activity map onto at least one axis of the vector basis; and searching for at least one local peak of acoustic activity in the map projection, an identified local peak corresponding to the presence of a sound source in the scene.

Abstract: A device and method for walker identification. An audio input interface obtains a sampled acoustic signal, possibly from a microphone, a vibration input interface obtains a sampled vibration signal, possibly from a geophone and at least one hardware processor fuses the sampled acoustic signal and the sampled vibration signal into a fused signal, extracts features from the fused signal and identifies a walker based on extracted features.

Abstract: A device and method for calculating scattering features for audio signal recognition. An interface receives an audio signal that is processed by at least one processor to obtain an audio frame. The processor calculates a first order scattering features from at least one audio frame and then calculates for the first order scattering features an estimation of whether the first order scattering features comprises sufficient information for accurate audio signal recognition. The processor calculates a second order scattering features from the first order scattering features only in case the first order scattering features does not comprise sufficient information for accurate audio signal recognition. As second order features are calculated only when it is deemed necessary, less processing power can be used by the device, which can lead to less power used by the device.