Principles and Applications of Speech Recognition Technology

Last week, Baidu announced that the entire range of voice technology interfaces will be permanently free, providing a multi-platform SDK (Software Development Kit) for voice recognition, voice synthesis, and voice wakeup, and will fully support developers and partners. Voice interaction is an important link between humans and machines. Baidu has announced that the full range of voice technology interfaces is permanently free, or it will bring about a huge industry revolution.
Intelligent voice technology is a key link in the artificial intelligence industry chain. Artificial intelligence industry chain is mainly divided into three levels. The bottom layer is infrastructure, including chips, modules, sensors, and big data platforms, cloud computing services, and network operators; the middle layer is a provider of basic technology research and services, including deep learning, computer vision, voice technology, and natural language processing. As well as robotics and other fields; the upper layer is the industry application, including smart home, wearable devices, driverless, virtual assistants, home robots and so on.
What is the principle of speech recognition technology?
The speech recognition system construction process includes two parts as a whole: training and recognition. Training refers to the signal processing and knowledge mining of pre-collected speech to obtain the "acoustic model" and "language model" required by the speech recognition system; the recognition is to automatically recognize the user's real-time speech. The identification process can usually be divided into two modules: "front end" and "back end": "front end" is mainly used for endpoint detection (removing excess mute and non-speech sound), noise reduction, feature extraction, etc.; "back end" The role is to use the trained "acoustic model" and "language model" to recognize the eigenvectors of the user's speech for statistical pattern recognition and to obtain the textual information it contains. In addition, the back-end module also has an "adaptive" feedback module that can perform self-learning on the user's voice to perform the necessary "correction" of the "acoustic model" and the "voice model" to further improve the recognition accuracy.
In what areas does intelligent voice technology play a role?
Smart Home: Finding the right voice portal is the key to unlocking the value of users behind smart homes. The hardware itself has an entry value, and smart speakers, smart TVs, home robots, etc., may all be suitable entrances. Through the front-end voice interaction to provide access to the back-end Internet to provide services in the way to complete the Internet of Things in the era of business scene mode conversion.
Smart Car: Voice interactions are just in the car scene and will be the first to break out. In the future, in-vehicle equipment providers can subsidize users to seize the automotive display market, collect and mine user vehicle behavior data, provide information for insurance companies and vehicle manufacturers, and insurance companies set up hierarchical premium mechanisms based on data to stimulate Regulate driving behavior. In this way, information flow and service flow will continue to flow in the ecosystem and continue to tap into greater value.

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