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Found 12 papers, 1 papers with code
Information Type Classification with Contrastive Task-Specialized Sentence Encoders
User-generated information content has become an important information source in crisis situations.
Classifying Dementia in the Presence of Depression: A Cross-Corpus Study
Automated dementia screening enables early detection and intervention, reducing costs to healthcare systems and increasing quality of life for those affected.
A Stutter Seldom Comes Alone -- Cross-Corpus Stuttering Detection as a Multi-label Problem
Most stuttering detection and classification research has viewed stuttering as a multi-class classification problem or a binary detection task for each dysfluency type; however, this does not match the nature of stuttering, in which one dysfluency seldom comes alone but rather co-occurs with others.
Dysfluencies Seldom Come Alone -- Detection as a Multi-Label Problem
This work explores an approach based on a modified wav2vec 2. 0 system for end-to-end stuttering detection and classification as a multi-label problem.
Influence of Utterance and Speaker Characteristics on the Classification of Children with Cleft Lip and Palate
Recent findings show that pre-trained wav2vec 2. 0 models are reliable feature extractors for various speaker characteristics classification tasks.
Multi-class Detection of Pathological Speech with Latent Features: How does it perform on unseen data?
The detection of pathologies from speech features is usually defined as a binary classification task with one class representing a specific pathology and the other class representing healthy speech.
An Acoustical Machine Learning Approach to Determine Abrasive Belt Wear of Wide Belt Sanders
This paper describes a machine learning approach to determine the abrasive belt wear of wide belt sanders used in industrial processes based on acoustic data, regardless of the sanding process-related parameters, Feed speed, Grit Size, and Type of material.
Nonwords Pronunciation Classification in Language Development Tests for Preschool Children
In this work, the task is to determine whether spoken nonwords have been uttered correctly.
The Influence of Dataset Partitioning on Dysfluency Detection Systems
This paper empirically investigates the influence of different data splits and splitting strategies on the performance of dysfluency detection systems.
Detecting Vocal Fatigue with Neural Embeddings
Vocal fatigue refers to the feeling of tiredness and weakness of voice due to extended utilization.
Compact Speaker Embedding: lrx-vector
Deep neural networks (DNN) have recently been widely used in speaker recognition systems, achieving state-of-the-art performance on various benchmarks.
Erlangen-CLP: A Large Annotated Corpus of Speech from Children with Cleft Lip and Palate
In this paper we describe Erlangen-CLP, a large speech database of children with Cleft Lip and Palate.
