Acoustic Model

Acoustic modeling focuses on representing and processing speech sounds for applications like speech recognition, synthesis, and emotion analysis. Current research emphasizes improving model robustness to noise and diverse acoustic conditions, exploring architectures like Transformers and convolutional neural networks, and developing techniques for efficient training and adaptation, including unsupervised and transfer learning methods. These advancements are crucial for enhancing the accuracy and reliability of speech-based technologies across various languages and applications, particularly in low-resource settings and healthcare.