In 2015, Microsoft and Google respectively released speech recognition systems based on deep learning. Among them, Microsoft's speech recognition system uses deep neural networks and a method called "time-delay neural network" to process speech signals. Google's speech recognition system uses a deep learning method called "end-to-end", which can directly convert speech signals into text.
The introduction of these deep learning-based speech recognition systems has greatly improved the accuracy and stability of speech recognition. For example, Google's speech recognition system has reduced the lithuania mobile database error rate of standard speech recognition test sets by about 30%, which is a major breakthrough in the field of speech recognition. In addition, these speech recognition systems have also promoted the development of intelligent voice assistants, such as Apple's Siri, Amazon's Alexa, and Google's Assistant.
The success of speech recognition technology based on deep learning has also promoted the application of deep learning technology in other fields. For example, natural language processing, computer vision and autonomous driving have all been widely used and rapidly developed by deep learning technology.
In March 2016, the AlphaGo artificial intelligence program developed by Google's DeepMind won the game against the Go world champion Lee Sedol, marking a breakthrough in the field of artificial intelligence in Go. This historic moment not only attracted media attention around the world, but also made deep learning technology more widely recognized and concerned in the field of artificial intelligence.