Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis | Paper Citation Record

Observation 996989fd-0ad4-471a-8883-8a02d55370d1 · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis wav2vec 2.0: A framework for self-supervised learning of speech representations

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.900635Z

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Observation 2c20c57d-0727-4a1e-a2f9-1923e9fcec21 · outbound

This paper cites Better speech synthesis through scaling.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Better speech synthesis through scaling

Reference 2

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Observation da4d6059-d957-4a40-b646-ed79e10e0d91 · outbound

This paper cites Audiolm: a language modeling approach to audio generation.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Audiolm: a language modeling approach to audio generation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.888991Z

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Observation 4da0a028-7968-46a2-afc0-d9ba82130442 · outbound

This paper cites SoundStorm: Efficient Parallel Audio Generation.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis SoundStorm: Efficient Parallel Audio Generation

Reference 4

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Observation 7b55b257-0531-481b-a2a2-e35416a02f23 · outbound

This paper cites Language models are few-shot learners.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Language models are few-shot learners

Reference 5

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Observation 9a4a5a56-897e-4fa7-b9fc-06b5aa821aa5 · outbound

This paper cites XTTS: a Massively Multilingual Zero-Shot Text-to-Speech Model.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis XTTS: a Massively Multilingual Zero-Shot Text-to-Speech Model

Reference 6

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Observation 5919ee56-1eeb-4d1f-91bd-83f1f5086090 · outbound

This paper cites A vector quantized approach for text to speech synthesis on real-world spontaneous speech.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis A vector quantized approach for text to speech synthesis on real-world spontaneous speech

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.870716Z

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Observation 10b39969-f666-4c5a-b2ea-c2d769da6ada · outbound

This paper cites ControlVC: Zero-Shot Voice Conversion with Time-Varying Controls on Pitch and Speed.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis ControlVC: Zero-Shot Voice Conversion with Time-Varying Controls on Pitch and Speed

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-09T16:43:09.467295Z

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Observation a98efccd-d824-4a27-a431-609124b0805e · outbound

This paper cites WavLM : Large-scale self-supervised pre-training for full stack speech processing.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis WavLM : Large-scale self-supervised pre-training for full stack speech processing

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.858766Z

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Observation 64796b72-25ba-44ed-891b-acb12ae1f5d4 · outbound

This paper cites Monotonic Chunkwise Attention.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Monotonic Chunkwise Attention

Reference 10

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Observation 683d8685-7551-4494-b098-9d356f18ddc0 · outbound

This paper cites Self-Supervised Speech Representations are More Phonetic than Semantic.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Self-Supervised Speech Representations are More Phonetic than Semantic

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.683147Z

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Observation 5139dc36-18d9-44d5-ba50-46c874ecb99d · outbound

This paper cites Unsupervised speech representation learning using wavenet autoencoders.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Unsupervised speech representation learning using wavenet autoencoders

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.846716Z

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Observation c92f5921-bb4d-4d35-94f6-ed3b4f674af5 · outbound

This paper cites VoxCeleb2: Deep Speaker Recognition.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis VoxCeleb2: Deep Speaker Recognition

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.690593Z

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Observation ae839e87-2861-4dfb-95c4-6c5d3455ef4d · outbound

This paper cites Simple and controllable music generation.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Simple and controllable music generation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.834722Z

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Observation 42fdbbb7-daf1-409b-a88d-65dfee838a79 · outbound

This paper cites The Road Less Scheduled.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis The Road Less Scheduled

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.697680Z

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Observation 78e54ebb-0f1c-4cfa-abdc-d34a57012c50 · outbound

This paper cites High Fidelity Neural Audio Compression.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis High Fidelity Neural Audio Compression

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.701299Z

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Observation bed1d918-2f40-4e9c-bc3c-40d2c9cb9140 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.705119Z

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Observation 145b50cf-72dd-4570-b187-3558c0682659 · outbound

This paper cites Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.709109Z

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Observation 80e6761d-857f-4f89-8d2c-491996350f99 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Taming transformers for high-resolution image synthesis

Reference 19

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Observation 0676804b-3905-4acf-9af2-bc1561793e37 · outbound

This paper cites Stochastic Backpropagation through Mixture Density Distributions.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Stochastic Backpropagation through Mixture Density Distributions

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-09T16:43:09.362124Z

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Observation 07aef043-1885-4302-95ac-421c5f748845 · outbound

This paper cites Robust Sequence-to-Sequence Acoustic Modeling with Stepwise Monotonic Attention for Neural TTS.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Robust Sequence-to-Sequence Acoustic Modeling with Stepwise Monotonic Attention for Neural TTS

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-09T16:43:09.344609Z

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Observation 51194fae-1175-4cfc-9e8f-699f97b9b500 · outbound

This paper cites Visqol: an objective speech quality model.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Visqol: an objective speech quality model

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.816607Z

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Observation 64c63cf4-faab-4277-91d3-8e1179154fa6 · outbound

This paper cites Reducing the dimensionality of data with neural networks.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Reducing the dimensionality of data with neural networks

Reference 23

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Observation 044afde6-530a-473f-b1fe-04bb4432fcf4 · outbound

This paper cites Hubert: Self-supervised speech representation learning by masked prediction of hidden units.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Hubert: Self-supervised speech representation learning by masked prediction of hidden units

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.799283Z

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Observation 15a21aac-fb50-487a-9384-360993f62109 · outbound

This paper cites Prodiff: Progressive fast diffusion model for high-quality text-to-speech.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Prodiff: Progressive fast diffusion model for high-quality text-to-speech

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.787597Z

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Observation 45b7547d-39b6-4a26-8dcc-0c14c4635439 · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Categorical Reparameterization with Gumbel-Softmax

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.738045Z

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Observation caa7e61c-5546-4f50-bd15-c1fdc9ccb94e · outbound

This paper cites Diff-TTS: A Denoising Diffusion Model for Text-to-Speech.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Diff-TTS: A Denoising Diffusion Model for Text-to-Speech

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.742096Z

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Observation 45da75a7-23fb-4c7e-9b49-c8ce4f8aeff1 · outbound

This paper cites Libri-light: A benchmark for asr with limited or no supervision.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Libri-light: A benchmark for asr with limited or no supervision

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.745908Z

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Observation ce42680e-7ba0-415e-bf82-450e533ba805 · outbound

This paper cites Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.769374Z

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Observation fffee71c-5db3-4f11-bb80-845d9355e870 · outbound

This paper cites Kingma and Max Welling.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Kingma and Max Welling

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.757721Z

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Observation 14cfdd7c-8655-4e06-9a7b-bdb201ac574c · outbound

This paper cites Hifi-gan: Generative adversarial networks for efficient and high fidelity speech synthesis.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Hifi-gan: Generative adversarial networks for efficient and high fidelity speech synthesis

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.745077Z

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Observation 1dd0fe29-c507-42f8-b1eb-2d084abfdc8c · outbound

This paper cites High-fidelity audio compression with improved rvqgan.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis High-fidelity audio compression with improved rvqgan

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.733435Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 982da5a7-6077-45ab-9c46-f5f50fe8ca29 · outbound

This paper cites Robust training of vector quantized bottleneck models.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Robust training of vector quantized bottleneck models

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.722906Z

Source-reported events for the cited work

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Observation 996e2d5b-fdd1-48d5-88b8-1a4ee0220a00 · outbound

This paper cites Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale

Reference 34

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Observation ceaace19-f2da-4f7a-97fc-c90eb85c1b64 · outbound

This paper cites HierSpeech++: Bridging the Gap between Semantic and Acoustic Representation of Speech by Hierarchical Variational Inference for Zero-shot Speech Synthesis.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis HierSpeech++: Bridging the Gap between Semantic and Acoustic Representation of Speech by Hierarchical Variational Inference for Zero-shot Speech Synthesis

Reference 35

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Observation 46734ece-16fc-4464-b22c-f7d03c37f3cb · outbound

This paper cites StyleTTS: A Style-Based Generative Model for Natural and Diverse Text-to-Speech Synthesis.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis StyleTTS: A Style-Based Generative Model for Natural and Diverse Text-to-Speech Synthesis

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.775875Z

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Observation a772db78-97fc-488d-8f3f-958bc6fe0134 · outbound

This paper cites Styletts 2: Towards human-level text-to-speech through style diffusion and adversarial training with large speech language models.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Styletts 2: Towards human-level text-to-speech through style diffusion and adversarial training with large speech language models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.779643Z

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Observation 2f6bd274-9071-430b-be9e-a69f1ff53512 · outbound

This paper cites JETS: Jointly Training FastSpeech2 and HiFi-GAN for End to End Text to Speech.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis JETS: Jointly Training FastSpeech2 and HiFi-GAN for End to End Text to Speech

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.783086Z

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Observation 0c3d4016-2a18-45d4-946d-7359cefedb8c · outbound

This paper cites DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.786889Z

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Unavailable: canonical work link unavailable.

Observation cd010cce-1125-4d87-ad1e-da6c7c2af2ce · outbound

This paper cites Natural language guidance of high-fidelity text-to-speech with synthetic annotations.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Natural language guidance of high-fidelity text-to-speech with synthetic annotations

Reference 40

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Observation 8215d38d-45e5-428f-88f1-99515e29df55 · outbound

This paper cites Adversarial Autoencoders.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Adversarial Autoencoders

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.794667Z

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Observation 674f8a57-6c60-49c6-974d-a887ccba5baa · outbound

This paper cites Should you use a probabilistic duration model in TTS? Probably! Especially for spontaneous speech.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Should you use a probabilistic duration model in TTS? Probably! Especially for spontaneous speech

Reference 42

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Observation 6975252e-218a-41d4-9a86-7e84fdf33352 · outbound

This paper cites Matcha-tts: A fast tts architecture with conditional flow matching.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Matcha-tts: A fast tts architecture with conditional flow matching

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.705074Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 88f18359-782a-4cf9-a878-cb14507d49a8 · outbound

This paper cites Finite Scalar Quantization: VQ-VAE Made Simple.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Finite Scalar Quantization: VQ-VAE Made Simple

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.805847Z

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Observation bbac4ca4-2011-4d0d-8c2e-0f07b4bba779 · outbound

This paper cites VoxCeleb: a large-scale speaker identification dataset.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis VoxCeleb: a large-scale speaker identification dataset

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.809872Z

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Observation c8705b49-25fa-4c1c-bb45-e288cfe5198a · outbound

This paper cites Librispeech: An ASR corpus based on public domain audio books.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Librispeech: An ASR corpus based on public domain audio books

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.693535Z

Source-reported events for the cited work

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Observation dc3fa77f-3c20-498f-ba72-4a1c1b184875 · outbound

This paper cites Speech Resynthesis from Discrete Disentangled Self-Supervised Representations.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Speech Resynthesis from Discrete Disentangled Self-Supervised Representations

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.817148Z

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Observation 24a6b9c0-c32b-4f2e-8ef5-16e955fb5f9a · outbound

This paper cites Grad-tts: A diffusion probabilistic model for text-to-speech.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Grad-tts: A diffusion probabilistic model for text-to-speech

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.682228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cfa424c9-5e9f-4027-a925-a560a4f0adb0 · outbound

This paper cites Autovc: Zero-shot voice style transfer with only autoencoder loss.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Autovc: Zero-shot voice style transfer with only autoencoder loss

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.670485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 10f2d27b-c147-4bc3-aa7d-83456ddd948e · outbound

This paper cites Language models are unsupervised multitask learners.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Language models are unsupervised multitask learners

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.827803Z

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Observation e5c149c6-979a-4f34-b0d0-349eee89c42f · outbound

This paper cites Robust Speech Recognition via Large-Scale Weak Supervision.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Robust Speech Recognition via Large-Scale Weak Supervision

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.831448Z

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Observation a5b6c15f-b284-4725-b56f-4229803b937d · outbound

This paper cites Online and linear-time attention by enforcing monotonic alignments.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Online and linear-time attention by enforcing monotonic alignments

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.649749Z

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Observation af00bcea-17c3-4890-a58c-a23e17cf1b72 · outbound

This paper cites Zero-shot text-to-image generation.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Zero-shot text-to-image generation

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.839506Z

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Observation 8554702d-e5e9-48f3-ba43-23f1330914cd · outbound

This paper cites Multi-task self-supervised learning for robust speech recognition.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Multi-task self-supervised learning for robust speech recognition

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.629301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 95547e88-ccb3-45cb-a924-52d7e9dc8f73 · outbound

This paper cites SpeechBrain: A General-Purpose Speech Toolkit.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis SpeechBrain: A General-Purpose Speech Toolkit

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.846652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1efd17cb-4407-4dad-9e1f-c1b4422746be · outbound

This paper cites Fastspeech: Fast, robust and controllable text to speech.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Fastspeech: Fast, robust and controllable text to speech

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.850283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30595c40-9843-41ae-99a8-e0c97676db0f · outbound

This paper cites FastSpeech 2: Fast and High-Quality End-to-End Text to Speech.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis FastSpeech 2: Fast and High-Quality End-to-End Text to Speech

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.853890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 527985ac-02ac-42d5-b1a4-e2b334c35561 · outbound

This paper cites PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.857847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e23dc9b-2bd6-467a-b18c-9d3f3979ccca · outbound

This paper cites Natural TTS synthesis by conditioning WaveNet on mel spectrogram predictions.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Natural TTS synthesis by conditioning WaveNet on mel spectrogram predictions

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.609529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1e86ae95-b1a8-4634-8fa5-ed966586445e · outbound

This paper cites Vae with a vampprior.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Vae with a vampprior

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.597826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 71b940c0-1f75-4b68-9f1e-4b0f1d62fbba · outbound

This paper cites Givt: Generative infinite-vocabulary transformers.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Givt: Generative infinite-vocabulary transformers

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.586523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 15dee1eb-a0c1-4600-9ac4-f2164726861f · outbound

This paper cites Neural discrete representation learning.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Neural discrete representation learning

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.574677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 854a2750-16f6-4ce2-99a7-b7fef754ed88 · outbound

This paper cites Attention is all you need.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Attention is all you need

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.875975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b5d92ce-8e0a-4d35-98be-214931992f8a · outbound

This paper cites Extracting and composing robust features with denoising autoencoders.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Extracting and composing robust features with denoising autoencoders

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.879511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8a9b278-1a99-4327-897c-8e491fe085be · outbound

This paper cites Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.882979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f3c0e47-517f-4968-9acf-ece206c86d17 · outbound

This paper cites Wespeaker: A research and production oriented speaker embedding learning toolkit.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Wespeaker: A research and production oriented speaker embedding learning toolkit

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.548600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 399ba5e1-aac2-4875-8197-67492879902a · outbound

This paper cites Tacotron: Towards End-to-End Speech Synthesis.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Tacotron: Towards End-to-End Speech Synthesis

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.890594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68e823fd-aa63-4bdf-baef-9f1b03201468 · outbound

This paper cites Soundstream: An end-to-end neural audio codec.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Soundstream: An end-to-end neural audio codec

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:43:09.536680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 56c7d2ab-042b-413e-8564-bb6deebe436a · outbound

This paper cites write newline.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis write newline

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.897920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79083430-95b0-4b2e-9170-49f5e7593ec0 · outbound

This paper cites @esa (Ref.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis @esa (Ref

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.903102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a613cc14-712e-429d-9e52-60008a2d4564 · outbound

This paper cites an unresolved cited work.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis Unresolved cited work

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.907509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0cf9e3f8-fc38-42de-ac12-fc96e9c01c22 · outbound

This paper cites 1.0" encoding=.

Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis 1.0" encoding=

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-09T16:43:08.911696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers