Research collaboration will reduce the risk of misunderstandings during emergency calls

The Luleå company Skyresponse and Luleå University of Technology are collaborating to develop automatic transcription of emergency calls with the help of AI.

Accelerates the analysis of emergency calls

Emergency lines are under high pressure and receive calls that are often noisy or of poor quality, or come from callers who speak a different dialect or mother tongue than the operator. These factors can jeopardize the operators’ ability to understand the calls and respond accordingly.

In such situations, operators could benefit greatly from support in the form of noise reduction and automatic real-time transcription. In addition, automatically created transcripts would have the added benefit of speeding up the analysis of emergency calls and the improvement of call handling protocols.

Facilitate the daily work of alarm operators

The aim of the project is to take the first steps towards an automatic transcription system that would help emergency call operators in real time during emergency calls and that would facilitate the analysis of these calls afterwards.

Erik Mattsson, who works in Applied research and development at Skyresponse, says:

“This feasibility study with Luleå University of Technology and the AI project Applied AI DIH North increases the skills of Skyresponse and has the potential to facilitate the daily work of alarm operators.”

He continues:

“It’s about fine-tuning trained models for speech to text. One hope is that in the long run it will enable a service that transcribes the alarm calls on an ongoing basis. Another hope is that the AI model can learn to hear what the alarmist says and reduce the risk for misunderstandings and possible delays in taking action. We would like to investigate whether the model can detect what is said better than the operator himself in case of unexplained sound.”

Alarm handling for different types of alarms

Skyresponse provides alarm handling. These are security alarms for the elderly and sick, personal alarms for those who may be exposed to threats or risky situations, but also alarms in connected Smart buildings and other IoT areas. An example is sensors that register smoke development when the system forwards it to the right person and alarm center, which then makes an assessment and can send fire brigades, guards or other personnel to the site.

AI assessment of alarms

In the long term, the company hopes that the work will form the basis for automatic translation of voice data, e.g. from a minority language to Swedish, to be able to receive and act on all voice alarms, regardless of language competence at the alarm center.

Erik Mattsson concludes:

“A more futuristic idea is that with AI technology we can in the long run create models that learn to recognize the semantics of the conversation, learn to have a dialogue with the caller and learn to understand what the relevant measures are.”