Computational methods for documenting and revitalising endangered Bharatiya languages: A proposed framework integrating speech processing, NLP, and community-driven digital platforms

More than 200 endangered Indian languages - in fact, most of them spoken by the so-called Particularly Vulnerable Tribal Groups (PVTGs) such as Juang in Odisha, Korku in Madhya Pradesh and Maharashtra, and Toda in the Nilgiris are facing extinction as a result of increasing linguistic homogenization caused by urbanisation and dominant lingua francas. Traditional methods of documentation, which rely heavily on manual transcription and static lexical resources, are not only laborious but also lack scalability and adaptability. In this paper, we propose an integrated computational framework that combines automatic speech recognition (ASR), natural language processing (NLP), and participatory digital platforms to not only document but also revitalise these languages systematically.

The proposed multimodal pipeline starts with ASR systems, which use transfer learning from Indic-specific models like IndicWav2Vec, to reach an estimated word error rate (WER) reduction of up to 85% on dialects like Odia-Sambalpuri that are not standardised by means of a dual-stage self-supervised pre-training on untranscribed field recordings. Along with this, transformer-based NLP modules will support morphology parsing and semantic role labelling, thus producing flexible, polysynthesis-aware dictionaries designed mainly for Dravidian and Munda languages. Also, an important community-oriented platform that will use open-source technologies such as Hugging Face Spaces and Flutter for cross-platform mobile accessibility, will make crowdsourced audio submissions via gamified interfaces that motivate users through the integration of language-learning modules.

In line with the spirit of the above sentence, here is a human-written one: Blockchain methods will be the foundation of data sovereignty by letting people decide the terms of governance access rights and generating ethical revenue streams from the use of datasets. Launching pilot projects focused on the Sambalpur district of Odisha will enable the collection of a 500-hour Sambalpuri dataset, which will be fed into a language revitalisation app expected to have over 2,000 simultaneous users, whose intergenerational transmission impact will be measured through user surveys. Determining system robustness will be done through the precise evaluation of computational experiments, including translation ability measured with BLEU scores and phoneme recognition accuracy. Following the ethical guidelines, three aspects will be considered simultaneously: audits for caste and gender bias, empowering the community members who are the co-researchers, and a qualitative survey that is just one of the ways to measure the impact of intergenerational transmission through a revitalisation app that, according to expectations, will have more than 2,000 users. The next phases include using neuro-symbolic methods to integrate code-switching and employing virtual reality (VR) experiences to increase the effectiveness of revitalisation.