FPGA Implementation for Speech Feature Extraction in Real Time
Aditya Deshmukh, Arman Khan, Vedika Patil, Kishor Barasu Bhangale · 2025
Speech recognition is vital for many human-computer interaction systems and Mel frequency cepstrum coefficients (MFCCs) plays vital role in feature extraction of the speech. This project aims to develop a Field Programmable Gate Array (FPGA) based application specific integrated circuit (ASIC) for extracting MFCCs from raw audio signals, and subsequently transmitting this feature data via USB to a laptop for further processing. MFCCs is widely used features in speech recognition, speaker identification, and other audio-based applications due to their ability to capture essential characteristics of the human voice. By extracting these features efficiently and transmitting them to a more powerful computing platform, this project seeks to provide a foundation for advanced speech processing tasks. The system will consist of an embedded platform (here, FPGA). It will be responsible for acquiring audio signals, performing pre- processing, extracting MFCC feature, and transmitting the feature data via USB to the laptop.