Speech Processing

Speech processing studies how computers can recognize words, identify speakers, understand vocal cues, and generate or improve speech. Common approaches include self-supervised speech encoders and Transformer or CTC models, alongside diffusion and flow-matching methods for synthesis, conversion, enhancement, and separation. Researchers evaluate these systems on tasks such as conversational transcription, speaker diarization, pronunciation assessment, and clinical speech analysis, increasingly including noisy, multilingual, and low-resource settings. A central challenge is making systems reliable across speakers, languages, and recording conditions while balancing accuracy and naturalness against latency, computation, privacy, and fairness.