Speech recognition using artificial neural networks and artificial bee colony optimization

Over the past decade or so, advances in machine learning have paved the way for the development of increasingly advanced speech recognition tools. By analyzing audio files of human speech, these tools can learn to identify words and phrases in different languages, converting them into a machine-readable format. While several machine learning-based models have achieved promising results on speech recognition tasks, they do not always perform well in all languages. For instance, when a language has a vocabulary with many similar-sounding words, the performance of speech recognition systems can decline considerably. Researchers at Mahatma Gandhi Mission's College of Engineering & Technology and Jaypee Institute of Information Technology, in India, have developed a speech recognition system to tackle this problem.