A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies | Paper Citation Record

Observation d2b59e89-d15c-4fee-bf0d-ad21db2c58f6 · outbound

This paper cites SoundStream: An End-to-End Neural Audio Codec.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies SoundStream: An End-to-End Neural Audio Codec

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:49.614160Z

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Observation cfb1e325-496f-4b72-ac7c-cf182fc1f6fb · outbound

This paper cites High Fidelity Neural Audio Compression.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies High Fidelity Neural Audio Compression

Reference 2

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Observation eedf5e07-1a5f-4115-ba13-f91b73f997d6 · outbound

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

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers

Reference 3

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Observation 1452ac3a-e68b-402c-a1ba-a499c7043767 · outbound

This paper cites Simple and Controllable Music Generation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Simple and Controllable Music Generation

Reference 4

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Observation 7e491632-8991-4cc2-ad95-7b3ec1c2ca39 · outbound

This paper cites UniAudio: An Audio Foundation Model Toward Universal Audio Generation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies UniAudio: An Audio Foundation Model Toward Universal Audio Generation

Reference 5

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Observation e8ddbbf9-7549-4140-81f6-76fd7ee31168 · outbound

This paper cites Moshi: a speech-text foundation model for real-time dialogue.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Moshi: a speech-text foundation model for real-time dialogue

Reference 6

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Observation b6e4639d-ccf9-4e20-b76d-7e15b40a3572 · outbound

This paper cites AudioLM: a Language Modeling Approach to Audio Generation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies AudioLM: a Language Modeling Approach to Audio Generation

Reference 7

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Observation 680aedd0-803b-4fae-9647-1e979396ba00 · outbound

This paper cites DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation

Reference 8

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Observation bba90d26-910c-41ad-b9f9-90b46d3d7161 · outbound

This paper cites Continuous Audio Language Models.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Continuous Audio Language Models

Reference 9

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Observation afa56b14-ca97-4c73-934b-d52173cce56f · outbound

This paper cites Cover and Joy A.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Cover and Joy A

Reference 10

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Observation c7c51330-02ac-4a8d-b75f-af6363632c44 · outbound

This paper cites UniAudio 1.5: Large Language Model-driven Audio Codec is A Few-shot Audio Task Learner.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies UniAudio 1.5: Large Language Model-driven Audio Codec is A Few-shot Audio Task Learner

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:47.882061Z

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Observation aa80f50f-65e4-460b-88ca-a6960e769793 · outbound

This paper cites The Information Bottleneck Method.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies The Information Bottleneck Method

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:49.491528Z

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Observation 1eead16d-e552-4c8d-8eb4-92aaee82e972 · outbound

This paper cites High-Fidelity Audio Compression with Improved RVQGAN.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies High-Fidelity Audio Compression with Improved RVQGAN

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:49.482247Z

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Observation 3fbad04c-68e5-4345-b72c-69ed12b0b7cb · outbound

This paper cites Discrete Audio Tokens: More Than a Survey! https://arxiv.org/abs/2506.10274, 2025.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Discrete Audio Tokens: More Than a Survey! https://arxiv.org/abs/2506.10274, 2025

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:47.893232Z

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Observation a8b297a1-93e5-4c46-bbc7-961cfe1ca123 · outbound

This paper cites HiFi-Codec: Group-residual Vector quantization for High Fidelity Audio Codec.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies HiFi-Codec: Group-residual Vector quantization for High Fidelity Audio Codec

Reference 15

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Observation f76e66a9-2689-4c01-92e5-6c5640ddb264 · outbound

This paper cites WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling

Reference 16

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Observation 418150a3-dc47-4c54-890e-6f658235067d · outbound

This paper cites BigCodec: Pushing the Limits of Low-Bitrate Neural Speech Codec.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies BigCodec: Pushing the Limits of Low-Bitrate Neural Speech Codec

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:47.903185Z

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Observation e241e6a3-07c9-4bc7-a7d6-21f9e446c9f6 · outbound

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

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Finite Scalar Quantization: VQ-VAE Made Simple

Reference 18

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Observation 6133a4c6-3614-43f3-8784-4bcd3ebf1084 · outbound

This paper cites SoundStorm: Efficient Parallel Audio Generation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies SoundStorm: Efficient Parallel Audio Generation

Reference 19

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Observation de8e945f-6794-4d3c-8279-d13c0ea79703 · outbound

This paper cites Masked Audio Generation using a Single Non-Autoregressive Transformer.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Masked Audio Generation using a Single Non-Autoregressive Transformer

Reference 20

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Observation ce1932c2-443a-457c-b121-0823992a3ee5 · outbound

This paper cites W2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies W2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:47.916888Z

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Observation ce5fab92-d7ab-452b-8292-797e3f8cf7d9 · outbound

This paper cites SpeechTokenizer: Unified Speech Tokenizer for Speech Large Language Models.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies SpeechTokenizer: Unified Speech Tokenizer for Speech Large Language Models

Reference 22

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Observation 2fab2696-b580-4295-94d8-0f055aad8f63 · outbound

This paper cites SoCodec: A Semantic-Ordered Multi-Stream Speech Codec for Efficient Language Model Based Text-to-Speech Synthesis.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies SoCodec: A Semantic-Ordered Multi-Stream Speech Codec for Efficient Language Model Based Text-to-Speech Synthesis

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-14T04:32:49.061753Z

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Observation a1c8901e-0f0d-4fb5-821c-77d2bf1fb045 · outbound

This paper cites SemantiCodec: An Ultra Low Bitrate Semantic Audio Codec for General Sound.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies SemantiCodec: An Ultra Low Bitrate Semantic Audio Codec for General Sound

Reference 24

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Observation fe5adde9-4640-45d3-b736-5a4b7939f957 · outbound

This paper cites Codec Does Matter: Exploring the Semantic Shortcoming of Codec for Audio Language Model.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Codec Does Matter: Exploring the Semantic Shortcoming of Codec for Audio Language Model

Reference 25

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Observation d49c1e6b-732d-4b39-9099-322895f7ec7b · outbound

This paper cites HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:47.948785Z

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Observation 0bde1496-b9f9-4427-b04e-13ff8dd373a2 · outbound

This paper cites WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:47.952821Z

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Observation fc6cf0c3-0130-4677-bd7b-856b8021eaa1 · outbound

This paper cites MOSS-Audio-Tokenizer: Scaling Audio Tokenizers for Future Audio Foundation Models.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies MOSS-Audio-Tokenizer: Scaling Audio Tokenizers for Future Audio Foundation Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:47.957531Z

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Observation 5c749d68-1735-49ff-8fa5-439b9cdb195d · outbound

This paper cites ALMTokenizer: A Low-bitrate and Semantic-rich Audio Codec Tokenizer for Audio Language Modeling.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies ALMTokenizer: A Low-bitrate and Semantic-rich Audio Codec Tokenizer for Audio Language Modeling

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:47.960877Z

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Observation 8cc305a7-31ff-49e2-aa1c-8c4aac5e2a48 · outbound

This paper cites Fewer-token Neural Speech Codec with Time-invariant Codes.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Fewer-token Neural Speech Codec with Time-invariant Codes

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:49.472237Z

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Observation 710342e8-7526-40e8-b051-35247d38dce7 · outbound

This paper cites Learning Source Disentanglement in Neural Audio Codec.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Learning Source Disentanglement in Neural Audio Codec

Reference 31

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Observation 0d93c519-337d-4f78-aefc-0f3d941c7728 · outbound

This paper cites NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:47.972389Z

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Observation 7b7d3346-a2e6-4982-a0b7-84125d828276 · outbound

This paper cites CosyVoice: A Scalable Multilingual Zero-shot Text-to-speech Synthesizer based on Supervised Semantic Tokens.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies CosyVoice: A Scalable Multilingual Zero-shot Text-to-speech Synthesizer based on Supervised Semantic Tokens

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:47.977209Z

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Observation 3c7dffe6-19b0-40ab-ab93-6df36700500a · outbound

This paper cites Seed-TTS: A Family of High-Quality Versatile Speech Generation Models.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Seed-TTS: A Family of High-Quality Versatile Speech Generation Models

Reference 34

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Observation 033e1daf-d353-4952-8593-68c7cffb7fd9 · outbound

This paper cites Stable Audio Open.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Stable Audio Open

Reference 35

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Observation 74619dc8-a967-49db-b4d2-5365e11688ff · outbound

This paper cites NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:47.991814Z

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Observation 02d37584-975e-4631-9d6e-7f81ba866280 · outbound

This paper cites Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models

Reference 37

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Observation 26ae9252-f018-422c-9de0-40b23401c289 · outbound

This paper cites DashengTokenizer: One layer is enough for unified audio understanding and generation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies DashengTokenizer: One layer is enough for unified audio understanding and generation

Reference 38

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Observation aed3a8ba-eff8-4564-9320-224800260784 · outbound

This paper cites WavCube: Unifying Speech Representation for Understanding and Generation via Semantic-Acoustic Joint Modeling.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies WavCube: Unifying Speech Representation for Understanding and Generation via Semantic-Acoustic Joint Modeling

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-14T04:32:48.784735Z

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Observation 2eecf9e9-4ac7-4739-aef3-27d356176657 · outbound

This paper cites Ming-UniAudio: Speech LLM for Joint Understanding, Generation and Editing with Unified Representation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Ming-UniAudio: Speech LLM for Joint Understanding, Generation and Editing with Unified Representation

Reference 40

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Observation 40e40133-7778-4238-a3be-cf5ab78ed5ca · outbound

This paper cites LoSATok: Low-dimensional Semantic-Acoustic Tokenizer for Cross-Domain Audio Understanding and Generation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies LoSATok: Low-dimensional Semantic-Acoustic Tokenizer for Cross-Domain Audio Understanding and Generation

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-14T04:32:48.735854Z

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Observation 7b5a52d9-2c0b-48f0-9dff-202af3ada8be · outbound

This paper cites Flow Matching for Generative Modeling.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Flow Matching for Generative Modeling

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.013264Z

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Observation bbde2eef-b8a9-41e2-9698-44f2f76c5e36 · outbound

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

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale

Reference 43

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Observation ee5b1124-7fb4-4fe3-b88b-661b823849cb · outbound

This paper cites GIVT: Generative Infinite-V ocabulary Transformers.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies GIVT: Generative Infinite-V ocabulary Transformers

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:49.459255Z

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Observation 68a66f64-d066-4465-8ea1-a405c4fcd8c5 · outbound

This paper cites Autoregressive Image Generation without Vector Quantization.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Autoregressive Image Generation without Vector Quantization

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:49.450189Z

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Observation 91e01e7c-9497-4c35-9fc3-4ad627ebc00b · outbound

This paper cites Hyperspherical Latents Improve Continuous-Token Autoregressive Generation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Hyperspherical Latents Improve Continuous-Token Autoregressive Generation

Reference 46

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Observation e0b217a0-0fd8-4229-af2f-fb3244eee52d · outbound

This paper cites MaskGIT: Masked Generative Image Transformer.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies MaskGIT: Masked Generative Image Transformer

Reference 47

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Observation 0cb337cd-8f82-4908-8d8b-8a0ec5dd4e6e · outbound

This paper cites Denoising Diffusion Probabilistic Models.Advances in Neural Information Processing Systems, 33:6840–6851, 2020.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Denoising Diffusion Probabilistic Models.Advances in Neural Information Processing Systems, 33:6840–6851, 2020

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.046526Z

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Observation a2e3b1db-8c91-4c9d-b78e-28678519f5bb · outbound

This paper cites Generative Spoken Language Modeling from Raw Audio.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Generative Spoken Language Modeling from Raw Audio

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.049500Z

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Observation 9c6e7a43-219d-442a-a9be-318988926923 · outbound

This paper cites Textually Pretrained Speech Language Models.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Textually Pretrained Speech Language Models

Reference 50

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Observation 7af9cea4-6af8-4ac6-8bbd-8c18142e4867 · outbound

This paper cites MusicLM: Generating Music From Text.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies MusicLM: Generating Music From Text

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.056851Z

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Observation 919576c7-bfbd-4e15-811f-af3c294d908c · outbound

This paper cites Diffsound: Discrete Diffusion Model for Text-to-sound Generation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Diffsound: Discrete Diffusion Model for Text-to-sound Generation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.060493Z

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Observation 992b07fb-5507-4222-ac29-6a397499279c · outbound

This paper cites InstructTTS: Modelling Expressive TTS in Discrete Latent Space with Natural Language Style Prompt.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies InstructTTS: Modelling Expressive TTS in Discrete Latent Space with Natural Language Style Prompt

Reference 53

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Observation 0e6decfd-b6b7-4b0d-9cd1-16704eff6bf9 · outbound

This paper cites E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.067554Z

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Observation a0bde76f-c503-4a1f-9568-0732554a0d40 · outbound

This paper cites F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.072180Z

Source-reported events for the cited work

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Observation 3592ff85-663b-4f84-b3af-417b3b73eb0b · outbound

This paper cites Autoregressive Speech Synthesis without Vector Quantization.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Autoregressive Speech Synthesis without Vector Quantization

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:49.434571Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation afc55e3d-a429-488d-a0ce-a9232926b084 · outbound

This paper cites VibeVoice Technical Report.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies VibeVoice Technical Report

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.078597Z

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Observation 14f27a22-bbf6-415a-801c-83a19178a63f · outbound

This paper cites DASB - Discrete Audio and Speech Benchmark.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies DASB - Discrete Audio and Speech Benchmark

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.082086Z

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Observation 695ee055-b283-4777-965a-4ecb5687dd40 · outbound

This paper cites TADA: A Generative Framework for Speech Modeling via Text-Acoustic Dual Alignment.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies TADA: A Generative Framework for Speech Modeling via Text-Acoustic Dual Alignment

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.085412Z

Source-reported events for the cited work

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Observation 586f54b3-7fb0-4dbc-9409-73fcce1625d8 · outbound

This paper cites FlexiCodec: A Dynamic Neural Audio Codec for Low Frame Rates.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies FlexiCodec: A Dynamic Neural Audio Codec for Low Frame Rates

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.088518Z

Source-reported events for the cited work

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Observation 3dac3314-cccf-4292-8650-377336324588 · outbound

This paper cites Signal Estimation from Modified Short-Time Fourier Transform, 1984.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Signal Estimation from Modified Short-Time Fourier Transform, 1984

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:49.426137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 90ad8a82-fbf4-4465-9083-21d17a99227b · outbound

This paper cites WaveNet: A Generative Model for Raw Audio.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies WaveNet: A Generative Model for Raw Audio

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.094769Z

Source-reported events for the cited work

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Observation fedec146-001e-4fd3-a522-7f5592eb1cef · outbound

This paper cites HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.098151Z

Source-reported events for the cited work

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Observation 12333eaf-8c9b-4265-8eb5-e5a2924e9724 · outbound

This paper cites Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.101601Z

Source-reported events for the cited work

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Observation d3082628-f791-459d-a9f3-4393e90dbd7d · outbound

This paper cites Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.105338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ebdef5a-ff7f-4971-8a60-b3fcdc44870e · outbound

This paper cites A Scale for the Measurement of the Psychological Magnitude Pitch.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies A Scale for the Measurement of the Psychological Magnitude Pitch

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.108713Z

Source-reported events for the cited work

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Observation 6a6fa749-8f53-4560-bb0e-e2523e919cb4 · outbound

This paper cites Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Sentences.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Sentences

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.114746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8d7505e-0465-4e84-a12b-19c646290737 · outbound

This paper cites WaveGrad: Estimating Gradients for Waveform Generation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies WaveGrad: Estimating Gradients for Waveform Generation

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:49.417145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5b0935a2-50dc-4572-a1b2-e851afb857f5 · outbound

This paper cites DiffWave: A Versatile Diffusion Model for Audio Synthesis.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies DiffWave: A Versatile Diffusion Model for Audio Synthesis

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:49.407635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a72bbb14-e7c8-4620-a0b5-4e100feb541b · outbound

This paper cites dMel: Speech Tokenization made Simple.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies dMel: Speech Tokenization made Simple

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.124613Z

Source-reported events for the cited work

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Observation b3fbabab-de1d-447a-af47-08297b6e5b09 · outbound

This paper cites Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.127905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9781d73b-e82d-432b-877d-83190c2d1675 · outbound

This paper cites DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.131468Z

Source-reported events for the cited work

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Observation e800c94e-5a30-402a-bb39-9e4aaf69d7ca · outbound

This paper cites Sound Texture Perception via Statistics of the Auditory Periphery: Evidence from Sound Synthesis.https://doi.org/10.1016/j.neuron.2011.06.032, 2011.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Sound Texture Perception via Statistics of the Auditory Periphery: Evidence from Sound Synthesis.https://doi.org/10.1016/j.neuron.2011.06.032, 2011

Reference 73

Resolution: verified exact; doi, observed 2026-08-14T04:32:48.194458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 454ad516-7a76-4550-b4c9-12049203e106 · outbound

This paper cites Neural Discrete Representation Learning.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Neural Discrete Representation Learning

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.140267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bc48978-6e4c-4923-b962-f8b1e1fb50c9 · outbound

This paper cites SNAC: Multi-Scale Neural Audio Codec.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies SNAC: Multi-Scale Neural Audio Codec

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.145931Z

Source-reported events for the cited work

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Observation 78417bdc-e7b6-4707-afd5-1877e1372cdd · outbound

This paper cites An Image is Worth 32 Tokens for Reconstruction and Generation.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies An Image is Worth 32 Tokens for Reconstruction and Generation

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:49.398032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9600fbcc-9f63-44c7-a359-952eb896998d · outbound

This paper cites FlexTok: Resampling Images into 1D Token Sequences of Flexible Length.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies FlexTok: Resampling Images into 1D Token Sequences of Flexible Length

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.155154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7282f635-559e-47c4-891b-d17a25385c20 · outbound

This paper cites Variable-rate discrete representation learning.

A Unifying Perspective on Audio Generative Modeling: Latent Representations and Modeling Strategies Variable-rate discrete representation learning

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:48.158348Z

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