An Automated Speech Recognition System Using Whale Optimized Random Forest Algorithm
Keywords:
Automated Speech Recognition (ASR), Whale Optimization Algorithm (WOA), Whale Optimized Random Forest Algorithm (WO-RFA), Mel Frequency Cepstral Coefficients (MFCC), natural language processingAbstract
Automated speech recognition (ASR) systems play a significant role in applications for natural language processing and human-computer interaction. The richness and variety of speech signals, however, make it difficult to improve the ASR systems' accuracy and effectiveness. This study describes an ASR system that uses the Whale Optimized Random Forest Algorithm (WO-RFA) algorithm to improve speech recognition performance. The suggested ASR system combines the strength of random forest algorithms with the optimization capabilities of the Whale Optimization Algorithm (WOA). The WOA is a nature-inspired metaheuristic algorithm based on humpback whale social behavior. It simulates whale hunting behavior to find the best solutions in a given search space. The system intends to improve the accuracy and resilience of speech recognition by incorporating WOA into the random forest algorithm. Noise removal, feature extraction, and normalization techniques are used to preprocess the speech data. This step gets the data ready for training and recognition. Preprocessed speech signals are analyzed to identify relevant information. The characteristics were extracted using MFCC, or Mel Frequency Cepstral Coefficients. To enhance the random forest's performance in voice recognition tasks, the WOA modifies the random forest's parameters and structure. To enhance the model's precision and effectiveness, the method alters hyper parameters such as the number of trees, tree depth, and splitting criteria. The ASR system incorporates the improved WORF model, allowing it to convert speech inputs into text outputs in real-time. The technology can be used for a variety of purposes, including voice assistants, transcription services, and voice-controlled systems.
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