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1
Defending Your Voice: Adversarial Attack on Voice Conversion ...
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2
FragmentVC: Any-to-Any Voice Conversion by End-to-End Extracting and Fusing Fine-Grained Voice Fragments With Attention ...
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3
Towards Unsupervised Speech Recognition and Synthesis with Quantized Speech Representation Learning ...
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4
From Semi-supervised to Almost-unsupervised Speech Recognition with Very-low Resource by Jointly Learning Phonetic Structures from Audio and Text Embeddings ...
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5
Improved Speech Separation with Time-and-Frequency Cross-domain Joint Embedding and Clustering ...
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6
Multi-target Voice Conversion without Parallel Data by Adversarially Learning Disentangled Audio Representations ...
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7
Almost-unsupervised Speech Recognition with Close-to-zero Resource Based on Phonetic Structures Learned from Very Small Unpaired Speech and Text Data ...
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8
Segmental Audio Word2Vec: Representing Utterances as Sequences of Vectors with Applications in Spoken Term Detection ...
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9
Phonetic-and-Semantic Embedding of Spoken Words with Applications in Spoken Content Retrieval ...
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10
Rhythm-Flexible Voice Conversion without Parallel Data Using Cycle-GAN over Phoneme Posteriorgram Sequences ...
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11
Improved Audio Embeddings by Adjacency-Based Clustering with Applications in Spoken Term Detection ...
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12
An Iterative Deep Learning Framework for Unsupervised Discovery of Speech Features and Linguistic Units with Applications on Spoken Term Detection ...
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13
A Multi-layered Acoustic Tokenizing Deep Neural Network (MAT-DNN) for Unsupervised Discovery of Linguistic Units and Generation of High Quality Features ...
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