Konkani is a resource-scarce language, mainly spoken on the west coast of India. The lack of resources directly impacts the development of language technology tools and services. Therefore, the development of digital resources is required to aid in the improvement of this situation. This paper describes the work on the Automatic Speech Recognition (ASR) System for Konkani language. We have created the ASR by fine-tuning the whisper-small ASR model with 100 hours of Konkani speech corpus data. The baseline model showed a word error rate (WER) of 17, which serves as evidence for the efficacy of the fine-tuning procedure in establishing ASR accuracy for Konkani language.