[Ads-l] Speech recognition for uncommon spoken languages

[Mark Mandel]

*Toward speech recognition for uncommon spoken languages*

*by Adam Zewe , Massachusetts Institute of Technology *

<
https://techxplore.com/news/2021-11-speech-recognition-uncommon-spoken-languages.html
>

*PARP is a new technique that reduces computational complexity of an
advanced machine learning model so it can be applied to perform automated
speech recognition for rare or uncommon languages, like Wolof, which is
spoken by 5 million people in West Africa. *

*Credit: Jose-Luis Olivares, MIT*

Automated speech-recognition technology has become more common with the
popularity of virtual assistants like Siri, but many of these systems only
perform well with the most widely spoken of the world's roughly 7,000
languages.

Because these systems largely don't exist for less common languages, the
millions of people who speak them are cut off from many technologies that
rely on speech, from smart home devices to assistive technologies and
translation services.

Recent advances have enabled machine learning models that can learn the
world's uncommon languages, which lack the large amount of transcribed
speech needed to train algorithms. However, these solutions are often too
complex and expensive to be applied widely.

Researchers at MIT and elsewhere have now tackled this problem 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.

Their technique 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 tweaks are needed
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 could help level the playing field and bring 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.

*Click headline for story*

------------------------------------------------------------
The American Dialect Society - http://www.americandialect.org