artificial neural networks to replace the modeling of H state posterior probability However due to the limited computing power at that time it was difficult to train a neural network model with more than two layers so the performance improvement it brought was very weak The development of machine learning algorithms and computer hardware over the past century has made it possible to train multihidden layer neural networks Practice shows that NN has achieved far superior recognition performance on various large data sets Therefore NNH replaces H and becomes the current mainstream acoustic modeling framework
Endtoend model Acoustic modeling of traditional speech recognition systems generally establishes the connection from the acoustic observation sequence to words through information sources such as articulatory units H acoustic models and dictionaries Each part requires separate learning and training steps which are cumbersome The endtoend EnEnEE structure uses a model to include these three information sources to Germany Telegram Number Data achieve direct conversion from observation sequences to text Some recent advances even include language model information to achieve better performance Since this year endtoend models have increasingly become a research hotspot in speech recognition 2 Language model Mainstream language models generally use statistical methods usually probabilistic models With the help
of model parameters the computer can estimate the likelihood of each sentence in natural language The statistical language model uses corpus training to emphasize that the corpus is the source of language knowledge Through indepth processing statistics and learning of the corpus the linguistic knowledge in natural language texts can be obtained so that subtle linguistic phenomena in largescale real texts can be objectively described Nr model Nr statistical language model is widely used in many fields due to its simplicity and easy understanding Speech models based on neural networks include three common language models feedforward neural network language
發表於 16:51:16
