Overlapped Speech Detection and Competing Speaker Counting–‐Humans Versus Deep Learning
A natural evolution of applications that analyze speech is to improve their robustness to multi-
speaker environments. Humans use selective auditory attention and can easily switch focus …
speaker environments. Humans use selective auditory attention and can easily switch focus …
[PDF][PDF] Predicting User Satisfaction from Turn-Taking in Spoken Conversations.
User satisfaction is an important aspect of the user experience while interacting with objects,
systems or people. Traditionally user satisfaction is evaluated a-posteriori via spoken or …
systems or people. Traditionally user satisfaction is evaluated a-posteriori via spoken or …
[PDF][PDF] Detecting Overlapped Speech on Short Timeframes Using Deep Learning.
The intent of this work is to demonstrate how deep learning techniques can be successfully
used to detect overlapped speech on independent short timeframes. A secondary objective …
used to detect overlapped speech on independent short timeframes. A secondary objective …
Depression severity estimation from multiple modalities
Depression is a major debilitating disorder which can affect people from all ages. With a
continuous increase in the number of annual cases of depression, there is a need to …
continuous increase in the number of annual cases of depression, there is a need to …
From Modular to End-to-End Speaker Diarization
F Landini - ar** speech is a natural and frequently occurring phenomenon in human–human
conversations with an underlying purpose. Speech overlap events may be categorized as …
conversations with an underlying purpose. Speech overlap events may be categorized as …
Can we detect speakers' empathy?: A real-life case study
In the context of automatic behavioral analysis, we aim to classify empathy in human-human
spoken conversations. Empathy underlies to the human ability to recognize, understand and …
spoken conversations. Empathy underlies to the human ability to recognize, understand and …