Speech Recognition Using Machine Learning Techniques

With the use of Machine Learning Algorithms, a fundamental task in Human-Computer Interaction, Speech Recognition has advanced significantly. The state-of-the-art in machine learning-based voice recognition is summarized in this abstract, which also covers the main challenges, contemporary advancements in the field, and important methodologies. By utilizing automated techniques, voice recognition utilizing machine learning entails translating spoken words into written text or commands. Voice-controlled devices, transcription services, virtual assistants, and other fields have all found use for this technology. The complexity of speech recognition problems has been successfully handled by machine learning techniques such as deep learning models. The abstract concludes by discussing current advancements in voice recognition research, such as end-to-end models, multitask learning, and the incorporation of contextual information from language models to improve the precision and usability of speech recognition systems. In summary, this abstract offers a thorough overview of speech recognition using machine learning, highlighting the developments, difficulties, and potential future directions of this topic that is quickly developing.