Search Results for author:
Found 12 papers, 3 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)
Spatial LibriSpeech: An Augmented Dataset for Spatial Audio Learning
We present Spatial LibriSpeech, a spatial audio dataset with over 650 hours of 19-channel audio, first-order ambisonics, and optional distractor noise.
Naturalistic Head Motion Generation from Speech
Synthesizing natural head motion to accompany speech for an embodied conversational agent is necessary for providing a rich interactive experience.
On the role of Lip Articulation in Visual Speech Perception
Previous research has shown that traditional metrics used to optimize and assess models for generating lip motion from speech are not a good indicator of subjective opinion of animation quality.
Learning Paralinguistic Features from Audiobooks through Style Voice Conversion
Paralinguistics, the non-lexical components of speech, play a crucial role in human-human interaction.
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.
Identifying Mood Episodes Using Dialogue Features from Clinical Interviews
Bipolar disorder, a severe chronic mental illness characterized by pathological mood swings from depression to mania, requires ongoing symptom severity tracking to both guide and measure treatments that are critical for maintaining long-term health.
Controlling for Confounders in Multimodal Emotion Classification via Adversarial Learning
Our results show that stress is indeed encoded in trained emotion classifiers and that this encoding varies across levels of emotions and across the lexical and acoustic modalities.
MuSE-ing on the Impact of Utterance Ordering On Crowdsourced Emotion Annotations
As a result, annotations are colored by the manner in which they were collected.
Improving End-of-turn Detection in Spoken Dialogues by Detecting Speaker Intentions as a Secondary Task
This work focuses on the use of acoustic cues for modeling turn-taking in dyadic spoken dialogues.
Capturing Long-term Temporal Dependencies with Convolutional Networks for Continuous Emotion Recognition
The goal of continuous emotion recognition is to assign an emotion value to every frame in a sequence of acoustic features.
Progressive Neural Networks for Transfer Learning in Emotion Recognition
Many paralinguistic tasks are closely related and thus representations learned in one domain can be leveraged for another.
