Method, apparatus and computer program product for determining the location of a plurality of speech sources

Sparse dictionary learning

Sparse dictionary learning (also known as sparse coding or SDL) is a representation learning method which aims at finding a sparse representation of the input data in the form of a linear combination of basic elements as well as those basic elements themselves. These elements are called atoms and they compose a dictionary. Atoms in the dictionary are not required to be orthogonal, and they may be an over-complete spanning set. This problem setup also allows the dimensionality of the signals being represented to be higher than the one of the signals being observed.

Compressed sensing

Compressed sensing (also known as compressive sensing, compressive sampling, or sparse sampling) is a signal processing technique for efficiently acquiring and reconstructing a signal, by finding solutions to underdetermined linear systems. This is based on the principle that, through optimization, the sparsity of a signal can be exploited to recover it from far fewer samples than required by the Nyquist–Shannon sampling theorem. There are two conditions under which recovery is possible.

Speech synthesis

Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products. A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic transcriptions into speech. The reverse process is speech recognition. Synthesized speech can be created by concatenating pieces of recorded speech that are stored in a database.

Method, apparatus and computer program product for determining the location of a plurality of speech sources

Graph Chatbot

Sparse Autoencoders for Speech Modeling and Recognition

Novel Methods For Detection And Analysis Of Atypical Aspects In Speech

Hardware Implementation of Digital Signal Processing Algorithms for Programmable Epilepsy Control Systems

Sparse Autoencoders for Speech Modeling and Recognition

Novel Methods For Detection And Analysis Of Atypical Aspects In Speech

Hardware Implementation of Digital Signal Processing Algorithms for Programmable Epilepsy Control Systems