System and method for generating impulse responses using neural networks

A computer implemented method for training a neural network architecture to generate an impulse response signal for a position in a 3D model of a room, the method comprising:

• obtaining a 3D model of the room comprising at least one sound source virtually emitting sound in the room;
• obtaining a training group of simulated impulse responses, wherein each simulated impulse response is generated for a respective predefined listening point in the 3D model of the room;
• training an autoencoder, the training comprising:
• training an encoder of the autoencoder by using the training group of simulated impulse responses as input in order to obtain a corresponding training group of compressed simulated impulse response as outputs;
• and
• training a decoder of the autoencoder by using the training group of compressed impulse responses as input in order to obtain a corresponding training group of uncompressed simulated impulse response as outputs;
• and
• training an IR neural network using the training group of compressed simulated impulse responses of the autoencoder and the corresponding position of the predefined listening points as input.

A system for generating an impulse response representing a sound wave propagation from at least one sound source received at a listening point in a room, the system comprising a computer system having processing circuitry coupled to a memory, and a neural network architecture coupled to the computer system, wherein the processing circuitry is configured to:

• obtain a generated impulse response at the listening point in the room from the neural network architecture by providing to the neural network architecture at least a position of the listening point as input, wherein the generated impulse response is generated using the neural network architecture trained according to:
• obtaining a 3D model of the room comprising the at least one sound source virtually emitting sound in the room;
• and
• obtaining a training group of simulated impulse responses, wherein each simulated impulse response is generated for a respective predefined listening point in the 3D model of the room;
• training an autoencoder, the training comprising:
• training an encoder of the autoencoder by using the training group of simulated impulse responses as input in order to obtain a corresponding training group of compressed simulated impulse responses as outputs;
• and
• training a decoder of the autoencoder by using the training group of compressed simulated impulse responses as input in order to obtain a corresponding training group of uncompressed simulated impulse responses as outputs;
• and
• training an IR neural network using the training group of compressed simulated impulse responses of the autoencoder and the corresponding positions of the predefined listening points as input.