National Edu News: Specialised Training Required for Implementing ECCE: Dr Venita Kaul  |  Cover Story: Elimination Round or Aptitude Test- How to Align CUET with NEP 2020 Goals  |  Life Inspirations: Master of a Dog House  |  Education Information: Climate Predictions: Is it all a Piffle!  |  Leadership Instincts: Raj Mashruwala Establishes CfHE Vagbhata Chair in Medical Devices at IITH   |  Parent Interventions: What Books Children Must Read this Summer Vacation   |  Rajagiri Round Table: Is Time Ripe for Entrepreneurial Universities in India?  |  Life Inspirations: How to Overcome Fear of Public Speaking  |  Teacher Insights: Guided Play Effective for Children  |  Teacher Insights: Doing Calculations Boosts Mental Strength  |  Best Practices: Hugging for Happiness  |  Parent Interventions: Is Frequent Childcare Outside of the Family Beneficial for a Child's Development  |  Health Monitor: How to Measure Attention?  |  Life Inspirations: From BC to AC: What Has Changed in Pandemic and What Has Not  |  Guest Column: The Biting Army  |  
November 05, 2021 Friday 11:51:20 AM IST

Automatic speech recognition developed by MIT

Researchers at MIT and elsewhere have tackled the problem of automated speech-recognition technology that don’t exist for less common languages by developing a simple technique that reduces the complexity of an advanced speech-learning model, enabling it to run more efficiently and achieve higher performance. The technique developed by the researchers of MIT involves removing unnecessary parts of a common, but complex, speech recognition model and then making minor adjustments so it can recognize a specific language. Because only small modifications are required once the larger model is cut down to size, it is much less expensive and time-consuming to teach this model an uncommon language. 

This work would be a help in the playing field of bringing automatic speech-recognition systems to many areas of the world where they have yet to be deployed. The systems are important in some academic environments, where they can assist students who are blind or have low vision, and are also being used to improve efficiency in health care settings through medical transcription and in the legal field through court reporting. Automatic speech-recognition can also help users learn new languages and improve their pronunciation skills. This technology could even be used to transcribe and document rare languages that are in danger of vanishing.  

Comments