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1
Speech Resynthesis from Discrete Disentangled Self-Supervised Representations
In: INTERSPEECH 2021 - Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-03329245 ; INTERSPEECH 2021 - Annual Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021)
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2
On Generative Spoken Language Modeling from Raw Audio
In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03329219 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2021 (2021)
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3
Generative Spoken Language Modeling from Raw Audio ...
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4
Generative Spoken Language Modeling from Raw Audio ...
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5
Textless Speech Emotion Conversion using Discrete and Decomposed Representations ...
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6
Self-Supervised Contrastive Learning for Unsupervised Phoneme Segmentation ...
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7
Phoneme Boundary Detection using Learnable Segmental Features ...
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8
The influence of lexical selection disruptions on articulation
In: J Exp Psychol Learn Mem Cogn (2018)
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9
Automatic Measurement of Pre-aspiration ...
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10
Learning Similarity Functions for Pronunciation Variations ...
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11
SEQUENCE SEGMENTATION USING JOINT RNN AND STRUCTURED PREDICTION MODELS
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12
Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks ...
Abstract: There is a lot of research interest in encoding variable length sentences into fixed length vectors, in a way that preserves the sentence meanings. Two common methods include representations based on averaging word vectors, and representations based on the hidden states of recurrent neural networks such as LSTMs. The sentence vectors are used as features for subsequent machine learning tasks or for pre-training in the context of deep learning. However, not much is known about the properties that are encoded in these sentence representations and about the language information they capture. We propose a framework that facilitates better understanding of the encoded representations. We define prediction tasks around isolated aspects of sentence structure (namely sentence length, word content, and word order), and score representations by the ability to train a classifier to solve each prediction task when using the representation as input. We demonstrate the potential contribution of the approach by analyzing ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/1608.04207
https://dx.doi.org/10.48550/arxiv.1608.04207
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13
Sequence Segmentation Using Joint RNN and Structured Prediction Models ...
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14
Automatic measurement of vowel duration via structured prediction ...
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15
Automatic measurement of vowel duration via structured prediction
Adi, Yossi; Keshet, Joseph; Cibelli, Emily. - : Acoustical Society of America, 2016
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16
VOWEL DURATION MEASUREMENT USING DEEP NEURAL NETWORKS
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