The role of speech recognition in reporting manual incidents
Nowadays, almost everyone knows about the latest advances on Artificial Intelligence (AI). We are very much aware of all the possibilities and benefits it can bring into our daily lives and into many industries. In today’s post, we will talk to you about the role of AI-based speech recognition systems in reporting manual incidents. Are you curious about the latest news about Artificial Intelligence? This is the place for you!
The situation of incident reporting
One of the most important duties police have to achieve is the instant transmission of information. Records management systems (RMS) and computer-aided dispatch (CAD) allow this to happen through technology. However, it is kind of challenging sometimes. This is because of the need to record all the information and retrieve data and details when an accident occurs. Incident reporting can be very time-consuming even though it is key to keep investigations and cases moving. According to a recent study, 50% of what police officers do is paperwork related to incident reporting. This means they spend most of the time entering data into a CAD or a RMS.
There are usually heavy documentation demands with short deadlines than can worsen the situation for police. This process can become inefficient and a barrier between the importance of the actual incident and its written representation. The goal of police reporting is to achieve consistency, detail and immediately capture the incidents. Another disadvantage of manual processes is the negative impact it can have on police officers. They have to spend a lot of time doing paperwork or even doing it while they are on patrol. Speech recognition systems can be the solution for this.
Speech recognition as the solution
Some police stations are implementing new reporting tools like speech recognition in order to solve issues related to the reporting of incidents. These are 3 ways these system can help police officers:
Improves the awareness of the situation
In any situation, it is key for a police officer to focus on her or his surroundings. However, if this person is performing tasks such as license plate lookups or entering data into the CAD/RMS, they are not focused. This type of situation can make the police officer more prone to accident or even an ambush. Having to enter data into a laptop while they are in the police car is not ideal either. Because of that, engineers have created tools like the Dragon Law Enforcement speech recognition. This way, officers use their voice to create reports and enter data without typing it themselves. With this solution, they become more aware of the situation around them and are safer.
Makes reports more specific and accurate
For police, to only rely on manual documentation is sometimes risky. This is because, according to studies, people usually forget 50% of the information presented to them within an hour. This percentage increases to 75% in 24 hours. For this reason, officers who respond to various incidents each day, need memory-recall or other type of notes everyday. These are obviously not always accurate, and sometime lack of specificity. Something that can concern the outcome of criminal proceedings related to incident reports. With the help of speech recognition, officers can perceive more details and build a narrative of every incident. Something crucial in order to get the best reporting possible.
Faster incident reporting
Accomplishing reporting deadlines is a vital part of police departments. If they do not do so, criminal proceedings can be stalled, or even abandoned. Speech recognition can also solve this issue. It can speed documentation and reporting deadlines due to its capabilities. This is because police officers only have to speak and not do manual work. Speech recognition is the solution is a police department is looking for high quality and accurate reports. This technology saves time and make the job way safer. There is absolutely no reason to miss this opportunity to increase productivity and and efficiency.
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