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SAR: Self-Supervised Anti-Distortion Representation for End-To-End Speech Model
In recent Text-to-Speech (TTS) systems, a neural vocoder often generates speech samples by solely conditioning on acoustic features …
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SAR: Self-Supervised Anti-Distortion Representation for End-To-End Speech Model
Dynamic Alignment Mask CTC: Improved Mask-CTC with Aligned Cross Entropy
Because of predicting all the target tokens in parallel, the non-autoregressive models greatly improve the decoding efficiency of …
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Dynamic Alignment Mask CTC: Improved Mask-CTC with Aligned Cross Entropy
Improving EEG-based Emotion Recognition by Fusing Time-frequency And Spatial Representations
Using deep learning methods to classify EEG signals can accurately identify people’s emotions. However, existing studies have …
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Improving EEG-based Emotion Recognition by Fusing Time-frequency And Spatial Representations
Improving Music Genre Classification from Multi-modal Properties of Music and Genre Correlations Perspective
Music genre classification has been widely studied in past few years for its various applications in music information retrieval. …
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Improving Music Genre Classification from Multi-modal Properties of Music and Genre Correlations Perspective
Learning Speech Representations with Flexible Hidden Feature Dimensions
Non-parallel many-to-many voice conversion is a kind of style transfer task in speech. Recently, AutoVC has been applied in this field …
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Learning Speech Representations with Flexible Hidden Feature Dimensions
QI-TTS: Questioning Intonation Control for Emotional Speech Synthesis
Recent expressive text to speech (TTS) models focus on synthesizing emotional speech, but some fine-grained styles such as intonation …
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QI-TTS: Questioning Intonation Control for Emotional Speech Synthesis
VQ-CL: Learning Disentangled Speech Representations with Contrastive Learning and Vector Quantization
Voice Conversion(VC) refers to converting the voice char- acteristics of audio to another one as it is said by other people. Recently, …
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VQ-CL: Learning Disentangled Speech Representations with Contrastive Learning and Vector Quantization
Feature-Rich Audio Model Inversion for Data-Free Knowledge Distillation Towards General Sound Classification
Data-Free Knowledge Distillation (DFKD) has recently attracted growing attention in the academic community, especially with major …
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Feature-Rich Audio Model Inversion for Data-Free Knowledge Distillation Towards General Sound Classification
Cross-grained Contrastive Representation for Unsupervised Lesion Segmentation in Medical Images
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Personalized Federated Learning via Gradient Modulation for Heterogeneous Text Summarization
Text summarization is essential for information aggregation and demands large amounts of training data. However, concerns about data …
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