A novel dual attention-based BLSTM with hybrid features in speech emotion recognition
Q Chen, G Huang - Engineering Applications of Artificial Intelligence, 2021 - Elsevier
Though the emotional state does not alter the content of language, it is a major determinant
in human communication, because it provides much more positive feedback. The purpose of …
in human communication, because it provides much more positive feedback. The purpose of …
An efficient speech emotion recognition based on a dual-stream CNN-transformer fusion network
The use of machine learning and artificial intelligence enables us to create intelligent
systems. Speech emotion recognition system analyzes the speaker's speech to determine …
systems. Speech emotion recognition system analyzes the speaker's speech to determine …
[HTML][HTML] Enhanced Indonesian ethnic speaker recognition using data augmentation deep neural network
K Nugroho, E Noersasongko - Journal of King Saud University-Computer …, 2022 - Elsevier
Speaker Recognition is a challenging topic in Speech Processing research area. The
various models proposed have succeeded in achieving a fairly high level of accuracy in this …
various models proposed have succeeded in achieving a fairly high level of accuracy in this …
Ethio-Semitic language identification using convolutional neural networks with data augmentation
In today's digital world, natural language is used to exchange information among humans,
and it has now advanced to the point of being an evolution criteria for technology. The …
and it has now advanced to the point of being an evolution criteria for technology. The …
Speech gender classification using bidirectional long short term memory
RD Alamsyah, S Suyanto - 2020 3rd International Seminar on …, 2020 - ieeexplore.ieee.org
Gender classification based on voice is crucial for speech recognition, which can be applied
to various applications. It is generally developed using conventional machine learning and …
to various applications. It is generally developed using conventional machine learning and …
Deep autoencoders for acoustic anomaly detection: experiments with working machine and in-vehicle audio
The growing usage of digital microphones has generated an increased interest in the topic
of Acoustic Anomaly Detection (AAD). Indeed, there are several real-world AAD application …
of Acoustic Anomaly Detection (AAD). Indeed, there are several real-world AAD application …
The Study of Malay's Prosodic Features Impact on Classical Arabic Accents Recognition
Modeling individual's variation in speech pattern can be challenging in Automatic Speech
Recognition (ASR). In Classical Arabic (CA) language, 20 Quranic accents are permitted for …
Recognition (ASR). In Classical Arabic (CA) language, 20 Quranic accents are permitted for …
Data augmentation and deep neural networks for the classification of Pakistani racial speakers recognition
Speech emotion recognition (SER) systems have evolved into an important method for
recognizing a person in several applications, including e-commerce, everyday interactions …
recognizing a person in several applications, including e-commerce, everyday interactions …
Speech recognition employing mfcc and dynamic time warping algorithm
Speech has been an integral part of human life acting as one of the five primitive senses of
the human body. As such any software or application based upon speech recognition has a …
the human body. As such any software or application based upon speech recognition has a …
Deep dense and convolutional autoencoders for machine acoustic anomaly detection
Recently, there have been advances in using unsupervised learning methods for Acoustic
Anomaly Detection (AAD). In this paper, we propose an improved version of two deep …
Anomaly Detection (AAD). In this paper, we propose an improved version of two deep …