3 accepted papers
One of the major requirements of automatic dubbing, as an extension of speech-to-speech translation, is isochrony. It refers to the fact that dubbed speech should line up in time with the original speech, matching the phrase-pause arrangement of the source utterance. To achieve this, we explore and…
In this paper, we study a simple yet elegant latent variable attention model for automatic speech recognition (ASR) which enables an integration of attention sequence modeling into the direct hidden Markov model (HMM) concept. We use a sequence of hidden variables that establishes a mapping from out…
Attention-based sequence-to-sequence models have shown promising results in automatic speech recognition. Using these architectures, one-dimensional input and output sequences are related by an attention approach, thereby replacing more explicit alignment processes, like in classical HMM-based model…