Industry Encyclopedia>Intelligent speech recognition
Intelligent speech recognition
2024-04-25 18:02:05
Intelligent Speech Recognition (ISR) is a technology that converts human speech into text or commands.
The technology is based on artificial intelligence and machine learning algorithms to identify speech content by analyzing the acoustic features and speech patterns of speech signals.
The core principle of intelligent speech recognition technology mainly includes the following steps: Voice signal acquisition: Voice signals are collected through devices such as microphones.
Preprocessing: Preprocessing the collected speech signal, including noise reduction, noise removal, etc, to improve the accuracy of recognition.
Feature extraction: Key acoustic features, such as Meir frequency cepstrum coefficient (MFCC), are extracted from pre-processed speech signals.
Model training: Using a large amount of speech data to train acoustic models and speech models, so that the system can accurately identify different people's pronunciation and language habits.
Speech recognition: The speech signal to be recognized is matched with a trained acoustic model and a language model to identify the speech content.
Intelligent voice recognition technology is widely used in many fields, such as: smart home: users can control home devices by voice, such as turning on and off lights, adjusting temperature, etc Vehicle system: The driver can navigate, play music and other operations through voice commands to improve driving safety.
Virtual assistant: Intelligent voice recognition technology can be integrated into the virtual assistant to help users query information, schedule, and so on.
Health care: Doctors can record medical records by voice, improving work efficiency; Patients can also interact with the medical system via voice to get health advice.
Financial services: Users can transfer funds and check balances by voice to improve their financial service experience.
With the continuous development of technology, intelligent speech recognition will become more and more accurate and efficient, bringing more convenience to people's lives.
The technology is based on artificial intelligence and machine learning algorithms to identify speech content by analyzing the acoustic features and speech patterns of speech signals.
The core principle of intelligent speech recognition technology mainly includes the following steps: Voice signal acquisition: Voice signals are collected through devices such as microphones.
Preprocessing: Preprocessing the collected speech signal, including noise reduction, noise removal, etc, to improve the accuracy of recognition.
Feature extraction: Key acoustic features, such as Meir frequency cepstrum coefficient (MFCC), are extracted from pre-processed speech signals.
Model training: Using a large amount of speech data to train acoustic models and speech models, so that the system can accurately identify different people's pronunciation and language habits.
Speech recognition: The speech signal to be recognized is matched with a trained acoustic model and a language model to identify the speech content.
Intelligent voice recognition technology is widely used in many fields, such as: smart home: users can control home devices by voice, such as turning on and off lights, adjusting temperature, etc Vehicle system: The driver can navigate, play music and other operations through voice commands to improve driving safety.
Virtual assistant: Intelligent voice recognition technology can be integrated into the virtual assistant to help users query information, schedule, and so on.
Health care: Doctors can record medical records by voice, improving work efficiency; Patients can also interact with the medical system via voice to get health advice.
Financial services: Users can transfer funds and check balances by voice to improve their financial service experience.
With the continuous development of technology, intelligent speech recognition will become more and more accurate and efficient, bringing more convenience to people's lives.
