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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.
OpenML: [494] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [495] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...
Pattern recognition has its origins in statistics and engineering; some modern approaches to pattern recognition include the use of machine learning, due to the increased availability of big data and a new abundance of processing power. Pattern recognition systems are commonly trained from labeled "training" data.
Sound recognition is a technology, which is based on both traditional pattern recognition theories and audio signal analysis methods. Sound recognition technologies contain preliminary data processing, feature extraction and classification algorithms. Sound recognition can classify feature vectors.
The journal covers research in computer vision and image understanding, pattern analysis and recognition, machine intelligence, machine learning, search techniques, document and handwriting analysis, medical image analysis, video and image sequence analysis, content-based retrieval of image and video, and face and gesture recognition.
Automatic target recognition (ATR) is the ability for an algorithm or device to recognize targets or other objects based on data obtained from sensors.. Target recognition was initially done by using an audible representation of the received signal, where a trained operator who would decipher that sound to classify the target illuminated by the radar.
Computer audition (CA) or machine listening is the general field of study of algorithms and systems for audio interpretation by machines. [1] [2] Since the notion of what it means for a machine to "hear" is very broad and somewhat vague, computer audition attempts to bring together several disciplines that originally dealt with specific problems or had a concrete application in mind.
Modular Audio Recognition Framework (MARF) is an open-source research platform and a collection of voice, sound, speech, text and natural language processing (NLP) algorithms written in Java and arranged into a modular and extensible framework that attempts to facilitate addition of new algorithms.