Speech recognition technology, also known as Automated Speech Recognition AutomaTIc Speech RecogniTIon (ASR), aims to convert vocabulary content in human speech into computer readable input such as buttons, binary codes or sequences of characters. Unlike speaker recognition and speaker confirmation, the latter attempts to identify or confirm the speaker who made the speech rather than the vocabulary content contained therein.
The speech recognition system prompts the customer to use the new password in a new situation so that the user does not need to remember the fixed password and the system will not be deceived by the recording. Text-related voice recognition methods can be classified into dynamic time warping or hidden Markov model methods. Text-independent voice recognition has been studied for a long time, and the performance degradation caused by inconsistent environments is a big obstacle in the application.
How it works:The dynamic time warping method uses instantaneous, variable scrambling. In 1963, Bogert et al. published "Sequence Scrambling Analysis of Echoes". By exchanging the alphabetical order, they define a new signal processing technique with a broad vocabulary, and the calculation of the cepstrum usually uses a fast Fourier transform.
Since 1975, hidden Markov models have become very popular. Using the hidden Markov model, the statistical variation of the spectral features is measured. Examples of text-independent speech recognition methods are average spectral method, vector quantization method, and multivariate autoregressive method.
The average spectral method uses a favorable scrambling distance, and the influence of the phoneme in the speech spectrum is removed by the average spectrum. Using vector quantization, the set of short-term training eigenvectors of the speaker can be used directly to describe the essential features of the speaker. However, when the number of training vectors is large, this direct depiction is impractical because the amount of storage and computation becomes bizarre. So try to use vector quantization to find an effective way to compress the training data. Montacie et al applied multivariate autoregressive mode to determine the speaker characteristics in the time series of scrambling vectors, and achieved good results.
I want to fool the speech recognition system to have a high-quality recorder, which is not very easy to buy. A typical recorder cannot record the complete spectrum of sound, and the quality loss of the recording system must also be very low. For most speech recognition systems, the imitation sound will not succeed. The use of speech recognition to identify identities is very complicated, so the speech recognition system will combine personal identification number identification or chip cards.
Speech recognition systems benefit from inexpensive hardware, and most computers have sound cards and microphones that are easy to use. But speech recognition still has some shortcomings. Voice changes over time, so biometric templates must be used. Voice can also change due to cold, hoarseness, emotional stress or puberty. Speech recognition systems have a higher false positive rate than fingerprint recognition systems because people's voices are not as unique and unique as fingerprints. For fast Fourier transform calculations, the system requires a synergistic processor and more performance than a fingerprint system. Currently, speech recognition systems are not suitable for mobile applications or battery powered systems.
Application field of speech recognition systemSpeech recognition system :
The application of speech recognition technology can be divided into two development directions: one is a large vocabulary continuous speech recognition system, which is mainly applied to computer dictation machines, and a voice information inquiry service system combined with a telephone network or the Internet. It is implemented on a computer platform; another important development direction is the application of miniaturization and portable voice products, such as dialing on wireless mobile phones, voice control of automobile equipment, smart toys, home appliance remote control, etc. Most of them are implemented using specialized hardware systems, especially the rapid development of ApplicaTIon Specific Integrated Circuit (ASIC) and the system of voice recognition system on chip (SOC) in recent years.
Application areas of speech recognition systems:
Speech recognition system application area: voice dialing for telephone communication
Especially in medium and high-end mobile phones, voice dialing is now common. As the price of the voice recognition chip decreases, the voice dialing function will also be available on the ordinary telephone.
Speech recognition system application field: car voice control
Since the driver's hand must be placed on the steering wheel while the car is in motion, making a call on the car requires a hands-free telephone communication with voice dialing. In addition, the operation of the car's satellite navigation and positioning system (GPS), the operation of the car air conditioner, lighting and audio equipment can also be conveniently controlled by voice.
Speech recognition system applications: industrial control and medical fields
When the operator's eyes or hands are already occupied, the best way to increase the control operation is to increase the human-machine's voice interaction interface. The voice is issued to the machine and the machine responds with a voice.
Speech recognition system application area: personal digital assistant
Voice interactive interface of Personal Digital Assistant (PDA). The size of the PDA is small, and the human-machine interface has always been one of the bottlenecks of its applications and technologies. Since the use of the keyboard on the PDA is very inconvenient, the handwriting recognition method is often used to input and query information. However, this method still makes the user feel inconvenient. Now the industry agrees that the best human-computer interaction interface of PDA is the interactive method of voice as the transmission medium, and there are a few applications. With the improvement of speech recognition technology, it is foreseeable that in the near future, speech will become the main human-computer interaction interface of PDA.
Speech recognition system application field: smart toys
Through speech recognition technology, we can talk to smart dolls, use voice to issue commands to toys, let them complete some simple tasks, and even create electronic watchdogs with voice lock. Smart toys have great market potential, and the key is to reduce the price of voice chips.
Speech recognition system application field: home appliance remote control
With voice, you can control the operation of TV, VCD, air conditioner, electric fan, curtains, and a remote control can control the electrical appliances in your home by voice. This can make the operation of various headaches easy. Row.
In addition to the applications mentioned above, the application of speech recognition chips in other areas can be said to be numerous. With the continuous improvement of the technology of the speech recognition dedicated chip, it will bring great convenience to people.
security service,outdoor camera security,home cameras,home security camera system
Dongguan Metalwork Technology Co., LTD. , https://www.dgdiecastpro.com