Language revitalization refers to the process of bringing a dead or dying language back into common usage. It is also called language revival, although many believe the term “revival” should only apply to dead languages and “revitalization” to dying ones.
Language reclamation is a related concept and frequently occurs together with revitalization/revival. However, it refers only to the process of a population reasserting its right to speak its language.
The main purpose of language revitalization is the preservation of culture. Reclamation of cultural heritage and strengthening of cultural identity are also common reasons for revitalizing languages—though many argue that this is not necessary to preserving cultural identification.
Another reason to revitalize or resurrect a language can include communication. However, this generally only occurs when there is no other widely spoken lingua franca.
Finally, linguists may support language revitalization efforts so they could increase the trove of linguistic data currently in existence. They may also find the data psychologically illuminating, as some linguistic concepts may be totally unique.
Of course, a language revival method must contain all the language’s data, in auditory and written form. When these do not exist, transcription and recording devices may help build up the data set. Deep learning techniques have helped build datasets like these in the past.
A good revitalization model may use UNESCO or other organizations’ data about the status of endangered languages. Examples of previous revivals or revitalizations would also be good choices. Depending on the state of the language—that is, whether it is “definitively endangered” or “critically endangered” according to UNESCO—some revitalization methods would be unhelpful.
Other important data may include gamification and other data used for e-learning methods; reviving a language depends on younger generations speaking it in everyday life, so engaging them with fun teaching methods may be critically important, especially if their parents do not speak the language well or at all.
Additionally, as noted earlier, some languages do not have complete written or auditory records. Artificial intelligence programs can identify individual words or parts of speech in a strange language and accurately record it for researchers and students.
The main challenge with this use case is that any revival or revitalization of a language depends on a large enough segment of a population to be willing to adopt a new language in everyday life, and carry that on for generations. The difficulty of this task is enormous—yet, when cultural heritage motivates people, it can be very effective.
Wal-aks, a knowledge holder fluent in the Nisga’a language who is advising on the language portion of the project, said using virtual reality would enhance the learning experience.
“I think that using those instruments would really contribute to being able to learn a lot more about our culture and our language when we’re able to see it,” Wal-aks said.
Semasio Audience Targeting uses the Semasio semantic approach to optimize marketing strategies. This approach uses records of keywords and phrases used by site visitors to create Semantic User Profiles. Then Semasio takes keyword and phrasal similarities in the browsing habits of established customers to create Seed Audiences that you can use to plan your marketing campaigns.
In each case, Semasio provides companies the ability to tailor their marketing approach with either specific or more general keywords.
Global Tone Communication AI Solutions provides video technologies and various NLP products, such as machine translation and speech recognition programs. This AI solution uses deep learning programs based on big data from around the web. Further industry applications include intelligent semantic search, chat robots, and recommendation systems.
Weborama BigSea uses semantic analysis across several languages to discover audience and consumer segments, detect purchase intent, and more
Semasio Contextual Targeting, based on their semantic approach which uses keywords and phrases of site visitors, optimizes marketing strategies. Semasio then uses that internal semantic information and customer browsing habits to create Seed Audiences that guide marketing campaigns.
In each case, Semasio provides companies the ability to tailor their approach using either specific or more general keywords.
Semasio Brand Fit Targeting uses the Semasio semantic approach to marketing and audience segmentation by using records of keywords and phrases used by site visitors to create Semantic User Profiles. With this data set, companies can also gain greater control over targeted campaigns by excluding what keyphrases and webpages from consideration.