Search Results for author:
Found 8 papers, 1 papers with code
ESPnet-SPK: full pipeline speaker embedding toolkit with reproducible recipes, self-supervised front-ends, and off-the-shelf models
First, we provide an open-source platform for researchers in the speaker recognition community to effortlessly build models.
Ranked #1 on
Speaker Verification
on VoxCeleb
(using extra training data)
Modality Dropout for Multimodal Device Directed Speech Detection using Verbal and Non-Verbal Features
Device-directed speech detection (DDSD) is the binary classification task of distinguishing between queries directed at a voice assistant versus side conversation or background speech.
Audiovisual Speech Synthesis using Tacotron2
The output acoustic features are used to condition a WaveRNN to reconstruct the speech waveform, and the output facial controllers are used to generate the corresponding video of the talking face.
Modality Dropout for Improved Performance-driven Talking Faces
We use subjective testing to demonstrate: 1) the improvement of audiovisual-driven animation over the equivalent video-only approach, and 2) the improvement in the animation of speech-related facial movements after introducing modality dropout.
On the Role of Visual Cues in Audiovisual Speech Enhancement
One byproduct of this finding is that the learned visual embeddings can be used as features for other visual speech applications.
On Neural Phone Recognition of Mixed-Source ECoG Signals
The emerging field of neural speech recognition (NSR) using electrocorticography has recently attracted remarkable research interest for studying how human brains recognize speech in quiet and noisy surroundings.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Speaker-Independent Speech-Driven Visual Speech Synthesis using Domain-Adapted Acoustic Models
We conclude that visual speech synthesis can significantly benefit from the powerful representation of speech in the ASR acoustic models.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
The Tutorbot Corpus --- A Corpus for Studying Tutoring Behaviour in Multiparty Face-to-Face Spoken Dialogue
The corpus is targeted and designed towards the development of a dialogue system platform to explore verbal and nonverbal tutoring strategies in multiparty spoken interactions.
