Computerized intelligent assistant for conferences
摘要
說明書
Non-limiting examples of training procedures for speech recognition machine 130 include supervised training, zero-shot, few-shot, unsupervised learning methods, reinforcement learning and/or generative adversarial neural network training methods. In some examples, a plurality of components of speech recognition machine 130 may be trained simultaneously with regard to an objective function measuring performance of collective functioning of the plurality of components in order to improve such collective functioning. In some examples, one or more components of speech recognition machine 130 may be trained independently of other components. In an example, speech recognition machine 130 may be trained via supervised training on labelled training data comprising speech audio annotated to indicate actual lexical data (e.g., words, phrases, and/or any other language data in textual form) corresponding to the speech audio, with regard to an objective function measuring an accuracy, precision, and/or recall of correctly recognizing lexical data corresponding to speech audio.
