ASMA

The proposed project aims to create an Integrated and Smart Automatic Speech Analysis System, with emphasis on its application in the medical sector, using modern Deep Learning and Neural Network techniques. The achievement of this will contribute significantly to the everyday processes of both medical and hospital staff, saving substantial resources (time, cost, etc.). As parallel goals are set the specialization of popular and/or new algorithms in the Greek language, as well as the achievement of a speech-to-Greek text automatic conversion engine that is qualitatively comparable to those in the literature, applicable both in specialized and general vocabulary — something not currently found in the scientific community and which constitutes a field of action with significant prospects.

Περίληψη έργου

As parallel goals are set the specialization of popular and/or new algorithms in the Greek language, as well as the achievement of a speech-to-Greek text automatic conversion engine that is qualitatively comparable to those in the literature, applicable both in specialized and general vocabulary — something not currently found in the scientific community and which constitutes a field of action with significant prospects.

Also targeted is the optimal conceptual extraction of metadata, without requiring training of learning models in every case.

Automatic speech analysis in medicine refers to the use of Natural Language Processing (NLP) and Speech Recognition (ASR) technologies, as well as Optical Character Recognition (OCR) to convert conversations and clinical notes into structured data.

These technologies, based on Artificial Intelligence and Neural Networks, allow health professionals to record, analyze, and extract information from oral communication without the need for manual transcription. For these reasons, the subject of the proposal aligns fully with Priority Sector ESEE 2021-2027: 08-ΨΤΕ: Digital Technologies, and specifically with Intervention Area 08.03.

Artificial Intelligence (AI) with priority 08.03.04 — AI systems by enterprises for the development of innovative products & services.

Automatic speech analysis in medicine has many applications that contribute to improving patient care and physician efficiency. Automatic speech analysis tools can convert conversations between doctors and patients into text, enabling automatic generation of clinical notes. This helps reduce the time spent on bureaucracy and increases the time doctors can devote to patients.

At the same time, these technologies can recognize speech patterns and keywords related to specific diagnoses, which can help in faster diagnosis of diseases, such as the detection of early signs of depression or dementia. In addition, speech analysis technologies can analyze voice tone and assess the patient’s mental state, providing valuable data to health professionals for evaluating the emotional state of patients.

Through the analysis of large volumes of speech data, hospitals and clinics can identify standardized care patterns and apply best practices, leading to better quality care and more targeted treatments.

The basis for building speech analysis models are Speech Recognition systems, which convert the audio signals of speech into text.

Purpose of the project

Who we are

InDigital S.A. was founded in 2000 and is a purely Greek technology company active in the field of Information Technology and development of electronic applications. Its basic mission is to provide innovative technological applications in a wide range of services, with the aim of pioneering through continuous research and investment in new, reliable technological solutions.

The goal is the development of the company at all levels through consistency and reliability of services toward its partners. Its long-term strategy is based on specialization in the IT sector and expansion into innovative technologies. For that reason, it continually strengthens its strategic alliances with other established and reliable companies, thus securing its leadership in its field of activity.

Its services are highly innovative for the Greek market, and it continuously invests in new service-enabling hardware and software using state-of-the-art technologies. It is comprised of experienced and reputable staff, most of whom have worked at the company for many years, resulting in full specialization in comprehensive partner service.

InDigital researches and develops IT projects fully adapted to the requirements of each project/partner, mainly based on open source software and applications it develops itself. For each project it undertakes, it proceeds to full documentation of requirements and investigates all possible technologies in order to present a complete final result.

Fields of activity

Development of algorithms and systems of Artificial Intelligence and Neural Networks
Digitization of archives & image processing technologies
Three-dimensional digitization of spaces and objects regardless of size
Development of virtual (VR) and augmented reality (AR) applications
Document management and document/workflow systems (InDMS)
Advanced remote digital signature service (InSign)
Integrated Information Systems for monitoring & managing information and publicity
Automatic transcription of medical reports
Technology for digital validation of receipts (DRVS)
Real estate & rent management systems
Systems for recording & managing requests
Development of information systems, web applications, specialized projects and apps
Robotic systems

Certifications

InDigital is certified with the most globally widespread Quality Management Standard, which sets the requirements for the development and implementation of an effective Quality Management System, ELOT EN ISO 9001-2015. It also holds the internationally recognized ELOT EN ISO 27001:2013 standard, which defines specifications for information security management. Moreover, it has the internationally recognized environmental management systems standard ELOT EN ISO 14001:2004. InDigital has participated in and executed many high-demand projects for both the public and private sectors.