research
Researchers develop controllable full-duplex speech model trainable on 2,000 hours of data
Researchers have developed F-Actor, an instruction-following full-duplex conversational speech model that can be trained efficiently on 2,000 hours of data without large-scale pretraining. The model enables explicit control over speaker voice, conversation topic, backchanneling, interruptions, and dialogue initiation, addressing naturalness limitations in current spoken conversational systems.