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Speech enhancement based on emphasizing the fundamental frequency integrated with SNMF/DNN
Single-channel speech enhancement is a popular problem in speech enhancement and related fields, but the traditional research direction is to improve...
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Meta-reinforcement learning based few-shot speech reconstruction for non-intrusive speech quality assessment
Speech quality assessment (SQA) is meaningful for modern communication systems and Quality of Service (QoS). At present, the non-intrusive SQA...
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Improving speech command recognition through decision-level fusion of deep filtered speech cues
Living beings communicate through speech, which can be analysed to identify words and sentences by recognizing the flow of spoken utterances....
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Schlieren imaging and video classification of alphabet pronunciations: exploiting phonetic flows for speech recognition and speech therapy
Speech is a highly coordinated process that requires precise control over vocal tract morphology/motion to produce intelligible sounds while...
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PublicVR: a virtual reality exposure therapy intervention for adults with speech anxiety
Speech anxiety, or Glossophobia, currently affects approximately 75% of the population with potentially severe negative effects on those with this...
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Robust Automatic Speech Recognition Using Wavelet-Based Adaptive Wavelet Thresholding: A Review
Automatic speech recognition (ASR) is one of the most fascinating fields of research and the performance of ASR systems is most promising in a closed...
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Speech Enhancement with Generative Diffusion Models
AbstractAn alternative approach to speech denoising using generative diffusion models that model the distribution of training data is proposed. In...
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Enhanced speech emotion recognition using averaged valence arousal dominance map** and deep neural networks
This study delves into advancements in speech emotion recognition (SER) by establishing a novel approach for emotion map** and prediction using the...
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Improvement of automatic speech recognition systems utilizing 2D adaptive wavelet transformation applied to recurrence plot of speech trajectories
Spectral-based features, typically used in ASR systems, do not capture the phase information of speech signals. Thus, exploiting new features that do...
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MetaRL-SE: a few-shot speech enhancement method based on meta-reinforcement learning
The goal of speech enhancement is to reduce and suppress the noise in noisy speech and improve the quality and intelligibility of damaged speech....
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A Novel Attention-Guided Generative Adversarial Network for Whisper-to-Normal Speech Conversion
Whispered speech is a special voicing style of speech that is employed publicly to protect speech information. It is also the primary pronunciation...
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HATS: An Open Data Set Integrating Human Perception Applied to the Evaluation of Automatic Speech Recognition Metrics
Conventionally, Automatic Speech Recognition (ASR) systems are evaluated on their ability to correctly recognize each word contained in a speech...
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Iterative-processed multiband speech enhancement for suppressing musical sounds
A multiband spectral subtraction (MBSS) processing step transforms background noise into annoying musical sounds. The paper proposes an...
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Semantic speech analysis using machine learning and deep learning techniques: a comprehensive review
Human cognitive functions such as perception, attention, learning, memory, reasoning, and problem-solving are all significantly influenced by...
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Adaptive attention mechanism for single channel speech enhancement
The recent development of speech enhancement methods has incorporated attention mechanisms for learning long-term speech signal dependencies. The...
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Ebola optimization based spiking neural network for automatic hate speech recognition
In this paper, efficient machine learning technique is introduced to develop efficient machine learning model for hate speech recognition from the...
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Man-Machine Speech Communication 17th National Conference, NCMMSC 2022, Hefei, China, December 15–18, 2022, Proceedings
This book constitutes the refereed proceedings of the 17th National Conference on Man–Machine Speech Communication, NCMMSC 2022, held in China, in...
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Deep Learning Algorithms for Speech Emotion Recognition with Hybrid Spectral Features
One of the popular research domains in Automatic Speech Recognition (ASR) is to identify emotions from the utterances of speech samples of human...
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CommanderUAP: a practical and transferable universal adversarial attacks on speech recognition models
Most of the adversarial attacks against speech recognition systems focus on specific adversarial perturbations, which are generated by adversaries...
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Segmentation of Noisy Speech Signals
AbstractOne of the most important problems in digital speech-signal processing is distinguishing segments of active speech and of background noise or...
