Speaker-Specific Lip to Speech Synthesis
7개 벤치마크 · 논문 4편 · 이 태스크의 논문 보기 →
Benchmarks
Most implemented
Densely Connected Convolutional Networks
Speech Reconstruction with Reminiscent Sound via Visual Voice Memory
Learning Individual Speaking Styles for Accurate Lip to Speech Synthesis
Papers
RobustL2S: Speaker-Specific Lip-to-Speech Synthesis exploiting Self-Supervised Representations
Significant progress has been made in speaker dependent Lip-to-Speech synthesis, which aims to generate speech from silent videos of talking faces. Current state-of-the-art approaches primarily employ non-autoregressive …
Lip to Speech SynthesisSpeaker-Specific Lip to Speech SynthesisSpeech SynthesisSpeech Reconstruction with Reminiscent Sound via Visual Voice Memory
The goal of this work is to reconstruct speech from silent video, in both speaker dependent and independent ways. Unlike previous works that have been mostly restricted to a speaker dependent setting, we propose Visual V…
Speaker-Specific Lip to Speech SynthesisLearning Individual Speaking Styles for Accurate Lip to Speech Synthesis
Humans involuntarily tend to infer parts of the conversation from lip movements when the speech is absent or corrupted by external noise. In this work, we explore the task of lip to speech synthesis, i.e., learning to ge…
Lip ReadingLip to Speech SynthesisSpeaker-Specific Lip to Speech SynthesisSpeech SynthesisDensely Connected Convolutional Networks
Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output. In…
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