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Found 14 papers, 0 papers with code
Investigating salient representations and label Variance in Dimensional Speech Emotion Analysis
Representations derived from models such as BERT (Bidirectional Encoder Representations from Transformers) and HuBERT (Hidden units BERT), have helped to achieve state-of-the-art performance in dimensional speech emotion recognition.
Pre-trained Model Representations and their Robustness against Noise for Speech Emotion Analysis
We investigated the use of pre-trained model representations for estimating dimensional emotions, such as activation, valence, and dominance, from speech.
Speech Emotion: Investigating Model Representations, Multi-Task Learning and Knowledge Distillation
We investigate the use of pre-trained model representations to improve valence estimation from acoustic speech signal.
Estimating Respiratory Rate From Breath Audio Obtained Through Wearable Microphones
Respiratory rate (RR) is a clinical metric used to assess overall health and physical fitness.
Analysis and Tuning of a Voice Assistant System for Dysfluent Speech
Dysfluencies and variations in speech pronunciation can severely degrade speech recognition performance, and for many individuals with moderate-to-severe speech disorders, voice operated systems do not work.
SEP-28k: A Dataset for Stuttering Event Detection From Podcasts With People Who Stutter
The ability to automatically detect stuttering events in speech could help speech pathologists track an individual's fluency over time or help improve speech recognition systems for people with atypical speech patterns.
Detecting Emotion Primitives from Speech and their use in discerning Categorical Emotions
Emotion plays an essential role in human-to-human communication, enabling us to convey feelings such as happiness, frustration, and sincerity.
Investigation and Analysis of Hyper and Hypo neuron pruning to selectively update neurons during Unsupervised Adaptation
This work investigates if pruning approaches are successful in detecting neurons that are either high-salient (mostly active or hyper) or low-salient (barely active or hypo), and whether removal of such neurons can help to improve the model's generalization capacity.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Leveraging Acoustic Cues and Paralinguistic Embeddings to Detect Expression from Voice
The expectation is that such assistants should understand the intent of the users query.
Articulatory and bottleneck features for speaker-independent ASR of dysarthric speech
The rapid population aging has stimulated the development of assistive devices that provide personalized medical support to the needies suffering from various etiologies.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Articulatory Features for ASR of Pathological Speech
In this work, we investigate the joint use of articulatory and acoustic features for automatic speech recognition (ASR) of pathological speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Articulatory information and Multiview Features for Large Vocabulary Continuous Speech Recognition
This paper explores the use of multi-view features and their discriminative transforms in a convolutional deep neural network (CNN) architecture for a continuous large vocabulary speech recognition task.
Interpreting DNN output layer activations: A strategy to cope with unseen data in speech recognition
This work proposes a strategy to assess a model's performance by analyzing the output layer activations by using a distance measure between the most likely target and the next most likely target, which is used for data selection for performing unsupervised adaptation.
Leveraging Deep Neural Network Activation Entropy to cope with Unseen Data in Speech Recognition
This work aims to estimate the propagation of such distortion in the form of network activation entropy, which is measured over a short- time running window on the activation from each neuron of a given hidden layer, and these measurements are then used to compute summary entropy.
