Speech

Contrastive Learning for improving End-to-end Speaker Verification
Speaker verification involves examining the speech signal to authenticate the claim of a speaker as true or false. Deep neural networks …
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ICSpk: Interpretable Complex Speaker Embedding Extractor from Raw Waveform
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When Hearing the Voice, Who Will Come to Your Mind
Speech is a carrier containing rich biological information, such as speaker identity information including age, gender, race. In this …
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A Real-Time Robot-Based Auxiliary System for Risk Evaluation of COVID-19 Infection
In this paper, we propose a real-time robot-based auxiliary system for risk evaluation of COVID-19 infection. It combines real-time …
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A Real-Time Robot-Based Auxiliary System for Risk Evaluation of COVID-19 Infection
Large-Scale Transfer Learning for Low-Resource Spoken Language Understanding
End-to-end Spoken Language Understanding (SLU) models are made increasingly large and complex to achieve the state-of-the-art accuracy. …
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Large-Scale Transfer Learning for Low-Resource Spoken Language Understanding
MLNET: An Adaptive Multiple Receptive-Field Attention Neural Network for Voice Activity Detection
Voice activity detection (VAD) makes a distinction between speech and non-speech and its performance is of crucial importance for …
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MLNET: An Adaptive Multiple Receptive-Field Attention Neural Network for Voice Activity Detection
A Robust Speaker Clustering Method Based on Discrete Tied Variational Autoencoder
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Evolutionary Algorithm Enhanced Neural Architecture Search for Text-Independent Speaker Verification
State-of-the-art speaker verification models are based on deep learning techniques, which heavily depend on the handdesigned neural …
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Prioritized Grid Highway Long Short-Term Memory-Based Universal Background Model for Speaker Verification
Prioritized grid long short-term memory (pGLSTM) has been shown to improve automatic speech recognition efficiently. In this paper, we …
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