5 Amazing Use Cases of Automatic Speech Recognition in NLP

By converting spoken language into text with high accuracy, ASR is powering tools that are used by millions of people around the world. Here are five of the standout uses of the technology.

1) Voice Assistants

ASR is at the core of voice-controlled assistants such as Alexa, Siri and the Google Assistant. These voice assistants rely on fast and accurate speech-to-text processing to interpret commands, answer questions and to interact with other applications. 

The NLP technology enables hands-free convenience and is rapidly being deployed across other use cases such as within cars, home appliances and workplace tools. 

ASR within cars is helping to improve safety, by enabling drivers to keep both hands on the wheel whilst operating commands such as changing the radio station or air conditioning settings.

2) Customer Service

Businesses and organisations around the world deploy ASR to automate call handling, transcribe their conversations and to generate insights into customer conversations. 

When combined with NLP sentiment analysis, ASR is helping companies to better understand their customers and to serve them more effectively and efficiently. 

ASR can be used as part of a process to detect frustration, improve agent training and streamline the resolution process. 

The result? Reduced operational costs and an improved customer experience.

3) Healthcare Documentation

Clinicians and healthcare professionals use ASR to dictate patient notes, prescriptions and medical records directly into digital systems. 

Patient care has always involved copious amounts of information that needs to both be secure and accessible by the right people. 

Physical paperwork is prone to get lost, hard to share round and difficult to update. ASR models trained on medical terminology are becoming a crucial part of modern electronic health record systems.

4) Accessibility

ASR has made real-time captioning a reality, without the need for specialist translators. Individuals with hearing difficulties have long been excluded from live events through no fault of their own. 

Now, ASR technology can be integrated into platforms such as Zoom and Microsoft Teams to provide automatic subtitles and ensure accessibility at scale.

5) Media and Content

The automatic transcription of podcasts, interviews and videos is repurposing long-form content, helping content creators to monetise their work and further their reach. 

This is vital to help support a thriving creator economy. This transcription functionality is also enabling searchable and indexable content. 

This is invaluable to journalists and researchers who need to quickly find and categorize information.

Custom ASR Projects

ASR might be commonplace within many industries, but the solutions vary significantly between use cases. General-purpose ASR systems cover a broad range of needs but often fall short within specialised environments. 

A voice assistant for an in-car system will have been trained very differently to an ASR solution used within the healthcare industry. 

Industries such as law, finance and education rely on highly technical vocabularies that generic models will struggle to recognise. Accents, regional dialects and industry-specific jargon only add to the complexity. 

Custom ASR model training solves these by creating sector specific solutions, ensuring they understand unique terminology and context. A legal ASR system will need to be able to know what habeas corpus is, whilst a medical solution will need to know the difference between Hydralazine vs Hydroxyzine. 

NetGeist specialise in the creation of custom ASR and NLP tools, designed with your use-case in mind. Our team creates tools that tackle textual challenges by automating, processing, and summarizing information. To discuss your requirements, contact us.