What is Natural Language Processing?
As we briefly covered in our articles on Speech To Text and Text To Speech technology, Natural Language Processing (NLP) is when software is designed to understand and also replicate human language, with huge benefits to how we live and work.
From a technical perspective, NLP uses artificial intelligence (AI) to capture data either by recording human speech or scanning a document. It then converts this information to machine language and applies algorithms to extract the meaning associated with each sentence. It can interpret the unstructured data, draw insights from it and convert it into structured data.
Combining the fields of computer science and linguistics (among others), NLP can be incredibly complex, as the process of breaking human languages down into units that a computer can understand is far more challenging than we may realise. The software that can comprehend and then respond to human-input text has to be highly sophisticated, but the software that can successfully listen to speech and then respond aloud is even more so.
Our writing presents ample difficulties for a computer to tackle; some languages feature highly varied grammatical structures, while slang terms constantly cycle in and out of our vocabulary… Add in the need to recognise spelling errors, and you’ll get an idea of how much of a challenge developing text-based NLP software has been. The words we say aloud are also affected by the speed and accent of the speaker, and homophones add yet more complexity into the mix too; consider how “I”, “eye” and “aye” all sound the same.
What can Natural Language Processing do?
NLP is a broad field, so its applications are hugely varied too. As well as dictation services and accessibility software, you’ll find NLP playing a role in online support services (including sites that pop up with a chatbot upon opening), voice assistants such as Alexa, Siri and the Google Assistant, along with autocorrect, predictive text, email spam filters and “related word” options in search engines.
Natural Language Processing in Healthcare
NLP’s potential in healthcare is especially exciting, as it is being used to create technology that will bring safety, accuracy and wellbeing to staff and patients alike. Applications include:
- Giving medical professionals access to key information hands-free through Text To Speech software
- Dictation services being used to take on the huge responsibility of medical notes
- Chatbot style tech can be used to triage patients at any stage deemed necessary
- NLP can identify key concepts or phrases in academic journals or clinical notes to summarise large quantities of data, ensuring health professionals have accurate and up-to-date information at hand
- Translating unstructured text into structured fields within electronic health records can improve clinical data integrity
- Predicting and identifying medical risks such as post-surgery complications, psychosis in schizophrenic patients, cancer and cirrhosis by processing and analysing patient records, medical history and clinical notes
Reduced wait times, more patient contact hours, improved medical outcomes and easier workloads can stem from the technology that Natural Language Processing is being used for… It’s sure to play a role in creating cohesive, effective and truly supportive experiences in the future of healthcare.