Show Me Your Face, And I'll Tell You How You Speak
This addresses the challenge of speaker identity-aware speech synthesis from visual cues, which is incremental as it builds on existing lip-to-speech methods.
The paper tackles the problem of generating speech from lip movements in unconstrained, large-vocabulary settings for multiple speakers, achieving accurate synthesis by conditioning on facial characteristics like age and gender.
When we speak, the prosody and content of the speech can be inferred from the movement of our lips. In this work, we explore the task of lip to speech synthesis, i.e., learning to generate speech given only the lip movements of a speaker where we focus on learning accurate lip to speech mappings for multiple speakers in unconstrained, large vocabulary settings. We capture the speaker's voice identity through their facial characteristics, i.e., age, gender, ethnicity and condition them along with the lip movements to generate speaker identity aware speech. To this end, we present a novel method "Lip2Speech", with key design choices to achieve accurate lip to speech synthesis in unconstrained scenarios. We also perform various experiments and extensive evaluation using quantitative, qualitative metrics and human evaluation.