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Dysfluencies Seldom Come Alone -- Detection as a Multi-Label Problem

Dysfluencies Seldom Come Alone -- Detection as a Multi-Label Problem

Sebastian P. Bayerl
Dominik Wagner
Florian Honig
Tobias Bocklet
Elmar Nöth
K. Riedhammer
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Papers citing "Dysfluencies Seldom Come Alone -- Detection as a Multi-Label Problem"

3 / 3 papers shown
Title
Boli: A dataset for understanding stuttering experience and analyzing stuttered speech
Boli: A dataset for understanding stuttering experience and analyzing stuttered speech
Ashita Batra
Mannas narang
Neeraj Kumar Sharma
Pradip K Das
41
0
0
27 Jan 2025
Optimizing Multi-Stuttered Speech Classification: Leveraging Whisper's Encoder for Efficient Parameter Reduction in Automated Assessment
Optimizing Multi-Stuttered Speech Classification: Leveraging Whisper's Encoder for Efficient Parameter Reduction in Automated Assessment
Huma Ameer
Seemab Latif
Iram Tariq Bhatti
38
1
0
09 Jun 2024
SEP-28k: A Dataset for Stuttering Event Detection From Podcasts With People Who Stutter
SEP-28k: A Dataset for Stuttering Event Detection From Podcasts With People Who Stutter
Colin S. Lea
Vikramjit Mitra
A. Joshi
S. Kajarekar
Jeffrey P. Bigham
45
94
0
24 Feb 2021