Automatic speech recognition (ASR), is one of the technologies focused on voice that has the greatest impact; it’s transforming the way students learn, employees work and society functions. ASR technology is also creating opportunities to assist specific communities of individuals, such as those navigating life or their studies with disabilities.
What is ASR?
Automatic speech recognition refers to technologies built to process human speech and turn it into text. The first take at speech recognition dates back to 1952 when Three Bell Labs researchers built a system called “Audrey” for single-speaker digit recognition.
Advanced versions of ASR transcription technologies now incorporate what is known as Natural Language Processing (NLP). These capture real conversations between people and use machine intelligence to process them. The accuracy provided by ASR is dependent on many factors, including speaker volume, background noise, the recording equipment used and more.
How does ASR transcription work?
Essentially, the process works as follows:
- An individual or a group speaks and an ASR software detects this speech.
- The device then creates a wave file of the words it hears.
- The wave file is cleaned to delete background noise and normalize the volume.
- This filtered wave form is then broken down and analyzed in sequences.
- The automatic speech recognition software analyzes these sequences and employs statistical probability to determine the whole words and then complete sentences.
- Some technology providers check the ASR’s work with professional human transcribers who correct any errors to achieve greater accuracy.
What is ASR used for?
ASR is being used in a variety of industries, such as higher education, legal, finance, government, health care and media where conversations are continuous and often need to be tracked or recorded word for word.
- Legal: In legal proceedings, it’s crucial to capture every word and there’s currently a shortage of court reporters. Digital transcription and the ability to scale are key solutions provided by ASR technology.
- Higher education: ASR allows universities to provide captions and transcriptions to students navigating hearing loss or other disabilities in classrooms. It can also serve the needs of students who are non-native speakers, commuters, or who have varying learning needs.
- Health care: Doctors are utilizing ASR to transcribe notes from meetings with patients or document steps during surgeries.
- Media: Media production companies use ASR to provide live captions and media transcription for all the produced, and must according to the FCC and other guidelines.
- Corporate: Companies are utilizing ASR for captioning and transcription to provide more accessible training materials and create inclusive environments for employees with differing needs.
What are the advantages of ASR transcription vs traditional transcription?
Aside from the growing shortage of skilled traditional transcribers, ASR machines can help to improve efficiencies for captions and transcriptions. The technology can differentiate between voices in conversations, lectures, meetings and proceedings to provide an understanding of who said what. The ability to differentiate between speakers can often be helpful since disruptions among participating parties are the norm in these conversations with multiple stakeholders.
Users can upload hundreds of related documents, including books, articles and more into the ASR machine to train it to get smarter. The technology can absorb this plethora of information faster than a human can, to begin recognizing different accents, dialects and terminology more accurately. Of course, the ideal format involves using human intelligence to fact check the artificial intelligence being used to meet the near-perfect accuracy required.
Additional benefits include:
- Improved information sharing with more data and for those who need accessible materials
- The ability to provide automatic transcription and captions for audio and video files to give immediate access to students, employees and consumers
- Creating more efficiencies that allow companies, such as legal agencies, to scale by providing more services to more clients quickly
- Easier documentation and hands-free note taking to help students and professionals
- Improved accuracy
How does Verbit’s ASR work specifically?
Verbit’s ASR machine works to provide captions and transcriptions for both live and recorded audio and video. It utilizes adaptive algorithms and three models which inform the ASR machine’s ability to perform precisely.
- An acoustic model reduces background noise and echo to cancel out factors that reduce the audio quality and identifies speakers
- A linguistic model identifies specific terminology, recognizes different accents and dialects and differentiates between speakers
- A contextual events model incorporates current events, news, and relevant updates
Verbit’s automatic speech recognition system works live or users can select to upload files after a recording is completed and then put the proprietary speech-to-text engine to work. Achieving accuracy is highly important to Verbit and its clients, and is often required by law. Verbit takes the process one step further by using two skilled human transcribers per project to edit and review the text produced by the ASR machine. This added human element allows us to seamlessly reach the 99% accuracy mark. The file can then be downloaded immediately for the client’s or student’s use.
ASR transcription technology is now expected and evolving
Consumers and professionals expect to reap the benefits and ease provided by devices that utilize automatic speech recognition. The days of jotting down notes by hand, figuring out which button turns the lights on and rushing home after forgetting to lock your home are gone. These tasks can all be completed with your voice and are then secured by technologies designed to differentiate one specific voice from others.
ASR software and ASR transcription services will only continue to disrupt the way we function in our classrooms, workplaces and homes. With more efficiencies and use cases, this technology will continue to evolve to best serve the individuals who have now come to rely on it.