Shabdocchar: K onkani W ord N et Enrichment with Audio Feature (2024)

Abstract: Konkani WordNet, also called Konkani Shabdamalem, was created as part of the Indradhanush WordNet Project Consortium between August 2010 and October 2013. Currently, the Konkani WordNet includes about 32,370 synsets and 37,719 unique words. There is a need to enhance the Konkani WordNet both quantitatively as well as qualitatively. In this paper we are presenting a Game-Based Crowdsourcing approach adopted by us to add audio feature to the Konkani WordNet which has resulted in an increase in the number of users using and getting exposed to the capabilities of the Konkani WordNet to aid in the Konkani language teaching-learning process as well as for creation of resources to initiate further research. Our work presented here has resulted in the creation of an audio corpus of 37,719 unique words which we have named as ‘Shabdocchar’ within a short time span of four months covering five dialects of Konkani. We are confident that Shabdocchar will prove to be a very useful resource to support future research work on Dialects of Konkani and support voice-based search of words in the wordnet. This approach can be adopted to enhance other wordnets as well.

## introduction the first wordnet, developed at princeton university foot_0 , was created for the english language. this was followed by the creation of wordnets for several european languages, such as the eurowordnet project @xcite . since the year 2000, efforts to build wordnets for various indian languages have gained momentum, starting with the hindi wordnet 2 , which was developed at the indian institute of technology, bombay(iitb). these efforts have expanded to include 2 introduction to konkani wordnet wordnet @xcite is essentially a large, graph-like structure of words. it serves as an electronic lexical database and is a valuable resource for researchers in fields such as computational linguistics, text processing, and other related nlp tasks. konkani wordnet @xcite was developed at goa university as part of the indradhanush wordnet consortium project funded by technology development for indian languages (tdil), department of electronics & information technology (deity), ministry of electronics & information technology (me-ity). in this project seven wordnets were constructed for seven indian languages namely bengali, gujarati, kashmiri, konkani, odia, punjabi and urdu using the expansion approach with hindi wordnet @xcite as the source. these seven wordnets were later linked to indowordnet @xcite . the ## game-based approach for audio corpus creation a simple web-based game was developed to allow konkani speakers to record the pronunciations of the konkani words. based on the number of words recorded for 15 minutes of time; they were awarded with the score. there are around 37,719 unique konkani words available in the konkani wordnet with unique ids which are further linked to the konkani synsets. the recording tool is developed such that the words displayed for pronouncing and the audio recordings are linked to each other. once the konkani word is displayed, a user has to pronounce it clearly and accurately. users can also listen to the recorded audio before saving and proceeding to the next word. the process goes on for 15 minutes and the users are awarded with scores based on the number of recordings they make in the given time slot. this interesting game is developed to capture and verify user-spoken words from the konkani wordnet. the application is built with a focus on user accessibility and audio quality control. the figure 1 shows how an app collects word pronunciations. the word allocator assigns words to users based on their dialect, ensuring that a word recorded in one dialect is also recorded by users in other dialects, so each word has pronunciations in all dialects. users record the words using a recording web interface and check the audio themselves for noise and clarity in a self-validation phase. once approved, the recording is saved to the cloud. it then goes through a quality enhancement process, and the improved version is also saved to the cloud. ## speech collection tool for audio corpus creation the pronunciation of each word was collected with the help of speech collection tool/game specially developed for this task. this game was played as a trial within the team of 5 konkani speakers and these pronunciations were validated in a later stage. entire activity went on for two weeks with a team of 5 members recording for 15 minutes a day for a week and crosschecking the recordings for 10 minutes a day during the consecutive week. as a result of this, pronunciations for 3,000 words out of 37,719 unique words of wordnet were recorded and validated. with this, the working of the game was tested and collected audio files were processed and linked to the wordnet. for the remaining 34,719 words, we used the crowd sourcing approach where a variety of goan konkani speakers from different regions, varying age groups and both the genders were requested to play the game and record the pronunciations for words in the konkani wordnet. ## results and discussion the contributions of this work can be broadly placed under the following three heads: ## future scope future enrichment of wordnets can be achieved by integrating multimodal resources, such as linking concepts to relevant images and real-world contexts, thereby enhancing their value in language learning and educational applications. gamified crowdsourcing can play a crucial role in accelerating this process by engaging a diverse user base through interactive tasks, leaderboards, and rewards while ensuring the collection of high-quality data. the use of generative ai to automatically create new glosses for concepts, coupled with gamified validation mechanisms, can further streamline the enhancement process. additionally, contemporary vocabulary, including regional variations and slang, can be systematically incorporated into wordnets to keep them relevant. the development of domain-specific wordnets tailored to fields like administration, medicine, law, and technology will also enable more precise and impactful applications in both research and industry.