How Speech Recognition Technology Works

Artificial intelligence voice recognition technology has begun to be widely used in modern society. This advanced technology allows people to control home appliances, lights, temperature and other items through voice commands. It not only improves the comfort of life, but also plays a huge role in fields such as healthcare, security and education. This article will use specific cases to deeply analyze the application of this technology in various fields and its positive significance to society.

01Smart Home With the development of Internet of Things technology and artificial intelligence voice recognition technology, smart home has become a part of people's lives. We can control various devices in smart home through voice commands, making our lives more convenient and energy-saving and environmentally friendly.

For example, voice commands can be used to open door locks, control lights, and adjust air conditioning, allowing people to directly hand over control to smart homes without having to manually operate devices when they return home.

In addition, artificial intelligence voice recognition technology also allows us to use home appliances through voice commands, such as smart TVs, drones, and smart speakers, etc. Just say the song, movie, or command you want to play to the device, and you can quickly meet your needs, making our lives more intelligent and efficient.

02Healthcare With the aging of the population and the continuous improvement of health awareness, the healthcare field has also ushered in an intelligent revolution. Artificial intelligence speech recognition technology is increasingly used in the healthcare field.

For example, the voice recognition technology of smartphones can help doctors accurately record medical history, condition and treatment plan, thus helping them to quickly make the correct diagnosis and treatment. This technology not only makes doctors' work more efficient, but also can greatly improve the quality of treatment and satisfaction of patients.

In addition, AI speech recognition technology can also be used in the management of healthcare institutions. For example, hospitals can use speech recognition technology to manage information such as doctors and staff schedules, patient visits, and drug reserves.

This helps to achieve efficient operation of healthcare institutions and balanced allocation of resources. At the same time, intelligent speech recognition technology can also be used for medical services such as voice assistants and virtual doctors, allowing patients to more easily access healthcare knowledge and services and better manage their own health.

03Security

In the security field, the application of artificial intelligence voice recognition technology can greatly improve security. Voice recognition technology can help people identify and control access rights to items to protect the security of homes, businesses and other places.

The technology can be used in handheld devices, smartphones, smart home systems, and integrated with devices such as security cameras.

In a home environment, intelligent voice recognition technology can help family members recognize each other's voices, thereby reducing the risk of theft. When a stranger enters the home environment, the system can automatically trigger an alarm to notify relevant personnel or the police.

In addition, voice recognition technology can also be used with devices such as smart door locks, making it easier for users to unlock their doors through voice commands. This use can make people's lives safer, more convenient and more intelligent.

In addition to homes, AI voice recognition technology is also widely used in corporate environments. For example, installing intelligent voice recognition equipment in large offices, shopping malls and other public places can help managers better understand the use of equipment and protect the security of important information.

In addition, voice recognition technology can also help security personnel identify customers and visitors, thereby ensuring the safety of the entire organization and personnel.

04 Education In the field of education, artificial intelligence speech recognition technology is also widely used. Speech recognition technology can be used in the classroom to help teachers and students communicate better, while promoting students' oral expression and listening skills.

For example, students can use intelligent speech recognition technology to record the teacher's explanation in class and use it as a review and learning material. In addition, some educational scholars and technology companies use artificial intelligence speech recognition technology to study children's speech development and language learning.

In addition, AI speech recognition technology can also be used to create educational tools, such as voice coaches or voice learning applications, to help students better master speaking skills. In language courses, students can use speech recognition technology to practice speaking, improve pronunciation and tone, and improve listening skills.

In short, the application of artificial intelligence speech recognition technology in the field of education will become more and more extensive. It can not only help students improve their oral skills, but also bring more useful innovations to the education industry.

Chatbots. It is not enough for robots to simply recognize language, they also need to understand and respond accurately. This response is not limited to voice, but may also extend to body movements, facial expressions, and even real emotions in the future.

Autonomous driving/unmanned driving. In the field of autonomous driving/unmanned driving, it is mainly an in-vehicle system. Now many car manufacturers have begun to add intelligent voice functions to their products, which can not only make calls and play music, but also enable navigation.

Wearable devices. Wearable devices with voice assistants can actually be understood as some kind of smart speaker products, with similarities and overlaps in functions. However, compared with home smart speakers, wearable devices are more convenient to carry, which also proves the name "wearable devices".

In general, in the era of artificial intelligence, the development of intelligent voice technology is an inevitable trend. Although various industry constraints are inevitable, they can be resolved through technological progress, financial support, policy encouragement and the development of the entire era. Therefore, the future of voice technology may not be a smooth road, but it is still bright. Speech recognition is mainly based on deep learning technology, and its entire process can be roughly divided into several key steps: sound signal processing, feature extraction, sound model training, language model training and recognition.

First, sound signal processing. Because the sound we emit is a continuous sound wave, in order to facilitate subsequent processing, we need to segment these continuous signals, which is the preprocessing of speech signals. The continuous sound should be divided into small segments, each of which is called a frame.

Then, feature extraction is performed. This is to extract the characteristic values ​​of each frame of sound, such as frequency, energy, etc. When we have these characteristic values, we can send them to the neural network for training, and then use the model to make predictions.

The next step is sound model training, which is to obtain the rules of pronunciation. Through a large amount of voice data, a deep neural network is trained to obtain a model that can predict the most likely pronunciation of a speech segment based on the characteristics of the speech.

After the sound model is trained, the language model is trained. The language model is mainly used to obtain the regularity of the language, such as which words often appear together, which words are followed by which words, etc. Through training with a large amount of text data, a model that can predict the rationality of sentences is obtained.

Finally, recognition is to decode the input speech based on the sound model and language model to obtain the most likely text result.

This process is like learning a new language. First, we break the language down into words, learn and understand their meanings one by one. Then, by mastering the language, we can understand and communicate in this language. Speech recognition is nothing more than letting machines do the same thing, except that the way of machine learning is to train data models and neural networks.