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The neural encoding of sound is the representation of auditory sensation and perception in the nervous system. [1] The complexities of contemporary neuroscience are continually redefined. Thus what is known of the auditory system has been continually changing.
Neural coding (or neural representation) is a neuroscience field concerned with characterising the hypothetical relationship between the stimulus and the neuronal responses, and the relationship among the electrical activities of the neurons in the ensemble.
Models of neural computation are attempts to elucidate, in an abstract and mathematical fashion, the core principles that underlie information processing in biological nervous systems, or functional components thereof. This article aims to provide an overview of the most definitive models of neuro-biological computation as well as the tools ...
The source–filter model represents speech as a combination of a sound source, such as the vocal cords, and a linear acoustic filter, the vocal tract.While only an approximation, the model is widely used in a number of applications such as speech synthesis and speech analysis because of its relative simplicity.
The model generates sounds through a neural network based synthesis, employing a WaveNet-style autoencoder to learn its own temporal embeddings from four different sounds. [2] [3] Google then released an open source hardware interface for the algorithm called NSynth Super, [4] used by notable musicians such as Grimes and YACHT to generate experimental music using artificial intelligence.
WaveNet is a deep neural network for generating raw audio. It was created by researchers at London-based AI firm DeepMind.The technique, outlined in a paper in September 2016, [1] is able to generate relatively realistic-sounding human-like voices by directly modelling waveforms using a neural network method trained with recordings of real speech.
These functionalities may utilise, for instance, (informed) audio source separation, speaker segmentation and identification, structural music segmentation, or social and Semantic Web technologies, including ontologies and linked open data. Speech recognition is an important semantic audio application.
Collecting Multibeam Sonar Data. Applications of sound source localization include sound source separation, sound source tracking, and speech enhancement. Sonar uses sound source localization techniques to identify the location of a target. 3D sound localization is also used for effective human-robot interaction. With the increasing demand for ...