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Paper Citation Record · LEDGER

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data

As of 18 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 1 inbound Pith citation observation for arXiv:2507.17735.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2507.17735 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:22:44.288042Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:22:44.084075Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-15T18:22:44.403714Z

Reference resolution

51 of 51 outbound references displayed

  • verified exact2
  • verified fuzzy40
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c3975430-fbed-4576-83e4-01ee1a97a853 · outbound

This paper cites We study the way to convert the non-native (L2) accented speech into a native (L1) accented one.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data We study the way to convert the non-native (L2) accented speech into a native (L1) accented one

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.993831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.078184Z digest=sha256:08e43eba07f3b8a9a467ba6ceaf36f64694a58bac42924adfa45814f87c4b313

Observation 56cec82a-4cef-4558-858a-aa341fa715e3 · outbound

This paper cites Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-15T18:22:44.408368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.084075Z digest=sha256:69e00eb331385a003ae1e14607980bdf7d04e686a3879928a6132c02368a973d

Observation 61f8d0ff-321b-425a-b5a6-a8cd11151c82 · outbound

This paper cites ours w/ dur. scaling.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data ours w/ dur. scaling

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.981049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.089066Z digest=sha256:b8918d464dfe7f93ccac2d71529f645d7b8cbb0112e0ab7efe269ca27fbb1153

Observation 778def70-d107-44d7-8230-baa755612bd5 · outbound

This paper cites an unresolved cited work.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-15T18:22:44.968855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.093800Z digest=sha256:1e23bdf28da8f8f2b7634e0ff6f653a84a3779406f8e00be19e5b21b0ee7f764

Observation 3a35856f-b650-4395-9c0f-15bcb6de2ab6 · outbound

This paper cites ours w/ dur. scal- ing.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data ours w/ dur. scal- ing

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.943990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.101541Z digest=sha256:9f79d1b30cefafff163ec680884adf3ae64691b1ce02a1a1b4145d08f0681214

Observation 4ff670ea-3c23-4794-a7eb-73c1f7daf46f · outbound

This paper cites Sub- jective evaluations on multiple English accents show signifi- cant improvements in speech naturalness, speaker similarity, and accentedness reduction.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Sub- jective evaluations on multiple English accents show signifi- cant improvements in speech naturalness, speaker similarity, and accentedness reduction

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.932448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.106378Z digest=sha256:e70ce25eab1b64e715a83c74f7ccbd3f93c1d6cc1ed1b0b143a8c5dd5c227385

Observation eed5d2f8-abeb-443c-99aa-112b3e1d02e8 · outbound

This paper cites 62401377), Shenzhen Science and Technology Program (Shenzhen Key Laboratory, Grant No.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data 62401377), Shenzhen Science and Technology Program (Shenzhen Key Laboratory, Grant No

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.920651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.110029Z digest=sha256:1c597beaac054a3dcb21b9f7d4493ff4a77755c1d8274be6383cf8fcdaff7804

Observation 276bb0fd-9576-4894-bf77-bb53e2aa1455 · outbound

This paper cites Vevo: Controllable zero-shot voice imitation with self-supervised disentanglement,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Vevo: Controllable zero-shot voice imitation with self-supervised disentanglement,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.827856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.143428Z digest=sha256:0176cf219262539b3a73f420e7ca686c430d67cebb26bc2c6964d5b8f2ca848c

Observation 32dd395b-2f87-46c1-8d9b-06f443fbcdd2 · outbound

This paper cites Foreign accent conversion in computer assisted pronunciation training,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Foreign accent conversion in computer assisted pronunciation training,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.908223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.113723Z digest=sha256:022853a97c9b94b87e8e130141a6218b280e291827e11c47a3fcfcc170f01836

Observation ddab51d9-aea5-4de6-acf0-616052ac06d9 · outbound

This paper cites Subband based voice conversion.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Subband based voice conversion

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.895245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.117092Z digest=sha256:97d9543a26bd45b0a4ed7f1030fd4fa40cece88c14ebd976f7b95878bf97e902

Observation 9e685838-fd25-4e6f-a716-4093d3c013e1 · outbound

This paper cites Personalized, cross-lingual tts using phonetic posteriorgrams.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Personalized, cross-lingual tts using phonetic posteriorgrams

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.881327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.121959Z digest=sha256:fb4295f7680ec08f5cc43adf154fa61d729c3929323fe732604f340c89bc41e1

Observation fc20b8c8-8a3d-47cd-9add-d79cbb06b44b · outbound

This paper cites Accent conversion using phonetic posteriorgrams,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Accent conversion using phonetic posteriorgrams,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.868318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.126050Z digest=sha256:aee3e280a6e9eaae7df87cafb352159fe81c81bbcfe3678f0b63d2ae990a8389

Observation ff37704f-983d-40b0-91e8-44ea64c958c1 · outbound

This paper cites Foreign accent con- version by synthesizing speech from phonetic posteriorgrams.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Foreign accent con- version by synthesizing speech from phonetic posteriorgrams

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.854211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.129970Z digest=sha256:a5e78dcc6e8f0b131ff78c3f867ee682b96e28ae5fb5fe667c9281a264ecbbd1

Observation 2e8ba706-5070-4157-8be8-d45adc0b54df · outbound

This paper cites Improving Accent Conversion with Reference Encoder and End-To-End Text-To-Speech.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Improving Accent Conversion with Reference Encoder and End-To-End Text-To-Speech

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-15T18:22:44.388217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.134317Z digest=sha256:c61d6154864816a72f68eb0e6664ade73a552b79841b9eb2c74299b7967626cc

Observation 43a07d9b-f74a-45a1-8efd-79845d7c6596 · outbound

This paper cites Accentron: Foreign accent conversion to arbitrary non-native speakers using zero-shot learning,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Accentron: Foreign accent conversion to arbitrary non-native speakers using zero-shot learning,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.840973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.138337Z digest=sha256:0710a437e07df876f723829d379ae7024b7c00332fb11b307e804e0b6ceac097

Observation 2be67f76-dc96-4d6f-b691-c3a75d9fb357 · outbound

This paper cites Tts-guided train- ing for accent conversion without parallel data,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Tts-guided train- ing for accent conversion without parallel data,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.722066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.176442Z digest=sha256:357e0ed71cdc354d511e40d9b68420968b3aae77308949b4bd43d182cc9b5186

Observation 1eff0d85-25f6-4cc0-a252-e7e094b3eba7 · outbound

This paper cites Converting foreign accent speech without a reference,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Converting foreign accent speech without a reference,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.816213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.147320Z digest=sha256:3519daab244d927f62f161492700fec3295952fdf4077a46dfa8cd3d2223ffa1

Observation ac67fef1-390c-4396-9a84-3559d5d27d90 · outbound

This paper cites Accent conversion using pre-trained model and synthesized data from voice conver- sion.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Accent conversion using pre-trained model and synthesized data from voice conver- sion

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.804947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.151718Z digest=sha256:711780a7bedc69aa29059cbb740cc5c1df63eaa78f698673e8ea1c82e1f6b6f1

Observation e21f3dda-ca92-4b7d-bed6-cd54fdd02776 · outbound

This paper cites Zero-shot foreign accent conversion without a native reference,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Zero-shot foreign accent conversion without a native reference,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.794364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.155872Z digest=sha256:ecad4a8327e287e6316e0889e2da9db22ee5d0e85d4c083db35c3affcc62e31a

Observation 84afe809-a601-4d5b-96fc-2a778d080f16 · outbound

This paper cites Evaluating methods for ground-truth- free foreign accent conversion,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Evaluating methods for ground-truth- free foreign accent conversion,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.783187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.160307Z digest=sha256:15108729ec1ee3adf8c926ed33ea87d090afed115b7910fc9b1e4a98c1c8e5b5

Observation b23200e9-efea-48e7-a1f0-7361508c5cb8 · outbound

This paper cites Convert and speak: Zero- shot accent conversion with minimum supervision,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Convert and speak: Zero- shot accent conversion with minimum supervision,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.769689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.164204Z digest=sha256:1be8fda51d056ecee97f6ca354fe7b0b6333d322011d785bd6575a4b09b617cc

Observation 6c3783ac-797f-4626-9910-6166e6be9c41 · outbound

This paper cites End-to-end accent conversion without using native utterances,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data End-to-end accent conversion without using native utterances,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.750692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.168611Z digest=sha256:c2b71538f05c339b003eeda945605b57346ce40c40a034bbf464249e370f5cc6

Observation db5273b6-fe9c-467f-91e5-71e6dadacb31 · outbound

This paper cites V oice-preserving zero-shot multiple accent conversion,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data V oice-preserving zero-shot multiple accent conversion,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.736587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.172533Z digest=sha256:8d7e8f93666872bf903790c737378f4fd02c9d04d89560fd9e3120534c66ab68

Observation 551b6c67-9f69-4645-9d52-2f4ed29c0804 · outbound

This paper cites Any-to-one sequence- to-sequence voice conversion using self-supervised discrete speech representations,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Any-to-one sequence- to-sequence voice conversion using self-supervised discrete speech representations,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.627207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.213053Z digest=sha256:c6cf38b0aaff34e622621e6a57889f551e32e70b9d1590e467a743c35c1d8f45

Observation 6b8092c5-9d89-4ce0-bad4-e7ae4e99d16a · outbound

This paper cites Zero-Shot Accent Conversion using Pseudo Siamese Disentanglement Network.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Zero-Shot Accent Conversion using Pseudo Siamese Disentanglement Network

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:44.180823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:44.180823Z digest=sha256:638feeb365bb124f55ec590e9cce61cdc9db6663c4546501cfc621f1cdecb874

Observation 7d038398-61a0-4d02-88d2-825e9810e180 · outbound

This paper cites Transfer the linguis- tic representations from tts to accent conversion with non-parallel data,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Transfer the linguis- tic representations from tts to accent conversion with non-parallel data,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.708102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.185466Z digest=sha256:8f2132cbf75179606df49b44d026daef183c6522ce12802c4f28d7a618bc1519

Observation d142cc54-931d-431c-8ebb-f9bde4e36cb3 · outbound

This paper cites Diffusion-based method with tts guidance for foreign accent con- version,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Diffusion-based method with tts guidance for foreign accent con- version,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.695099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.190194Z digest=sha256:8012f2a1fd652a22a1425aa12756e60d966d77ae2f58b48ad0256644f034993d

Observation f1bb62d3-d28b-4792-bc05-06a1a5adec2c · outbound

This paper cites Improving pronunciation and accent conversion through knowledge distilla- tion and synthetic ground-truth from native tts,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Improving pronunciation and accent conversion through knowledge distilla- tion and synthetic ground-truth from native tts,

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:44.197154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:44.197154Z digest=sha256:c85c9580ff480f0201b4493e1650bde35867cbfb9c3ebd9c02cc4ba370ab5990

Observation 93e0bdbd-fea5-4e21-951a-438a3825d7c6 · outbound

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

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Hubert: Self-supervised speech repre- sentation learning by masked prediction of hidden units,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.670664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.201095Z digest=sha256:bffc382db4bae4248f5baaaadb547952bbca1b55d66f4ca9018e93c2581b4ee4

Observation e86603e3-302c-4908-ae3e-1dd560df7a05 · outbound

This paper cites Self-supervised speech representations are more phonetic than semantic,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Self-supervised speech representations are more phonetic than semantic,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.654722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.205084Z digest=sha256:e9b5d9ec0c8bcffdec8b539eb57a543aa3ed6096a7910dea1f8fb67428456496

Observation 55bedc40-1416-4a90-b941-d2007574abfa · outbound

This paper cites Speak, read and prompt: High- fidelity text-to-speech with minimal supervision,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Speak, read and prompt: High- fidelity text-to-speech with minimal supervision,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.640532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.209120Z digest=sha256:5028d3d354a43eca05ff39bde08ac46160f1a12097fe66b16c32ff9bc8aab56b

Observation 006d32be-db8a-421b-9ae4-7978ca7dcc82 · outbound

This paper cites Total-duration-aware duration modeling for text-to-speech systems,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Total-duration-aware duration modeling for text-to-speech systems,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.553734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.245517Z digest=sha256:1ae45556db1e39f8b428f58247467e7d89d4254f13712cc2f551f5b43546087f

Observation e3979e28-8e47-487a-afcd-bfb7809cb329 · outbound

This paper cites On generative spoken language modeling from raw audio,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data On generative spoken language modeling from raw audio,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.614580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.217035Z digest=sha256:fdb70ec8e05bd5e24fcd9040c2f3b5574683dd8b7f1a5fe72db371fbd85e979b

Observation 4c4142f0-b2f0-4b25-a19e-04e235711b2f · outbound

This paper cites Direct speech-to-speech translation with discrete units,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Direct speech-to-speech translation with discrete units,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.601000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.220809Z digest=sha256:176852b614be666dad081458f1ca6c1bc50eef323e61f9c498e81db460a8cb52

Observation e8048819-f9d5-4b44-b9d1-b147f6b4654e · outbound

This paper cites LLaMA-Omni: Seamless Speech Interaction with Large Language Models.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data LLaMA-Omni: Seamless Speech Interaction with Large Language Models

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:44.224384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:44.224384Z digest=sha256:f9f54081399046b8ff4eb92314b07a767d72d491831e1cfe3f004530745e572b

Observation 423988f5-8d12-4902-9d89-7fd51d4dbd8b · outbound

This paper cites Flow matching for generative modeling,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Flow matching for generative modeling,

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:44.228599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:44.228599Z digest=sha256:8c4944d8f212151cf12c6baaff5a799c59e5a723d03a10a035f0f05a742933c3

Observation 83a8a10a-82d9-4573-a6ce-06880d9101a2 · outbound

This paper cites Matcha-tts: A fast tts architecture with conditional flow match- ing,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Matcha-tts: A fast tts architecture with conditional flow match- ing,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.580887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.232685Z digest=sha256:05e41c4b16c13beb618a690aca6dea91878bbf3a23e23523444e2f4e5cfb3e6f

Observation 7c256243-c2ab-4ad1-973c-c11bbec24b54 · outbound

This paper cites V oicebox: Text-guided multilingual uni- versal speech generation at scale,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data V oicebox: Text-guided multilingual uni- versal speech generation at scale,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.568032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.236919Z digest=sha256:f55052a72fcc4cb3a267b80f6af5443aae40dcd65f895ef659e6653b3abb6eaf

Observation bdd2d72a-4063-42f1-a544-cc44a7258273 · outbound

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

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:44.240684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:44.240684Z digest=sha256:8987b1a997feb9bfdc3fce55650946505b8426d4bdb6b58b58e8a6f657863bfa

Observation 0b4172e9-2304-4f50-9151-bdf4a2a31eac · outbound

This paper cites BigVGAN: A universal neural vocoder with large-scale train- ing,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data BigVGAN: A universal neural vocoder with large-scale train- ing,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.462267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.275275Z digest=sha256:5fb38c15178bf89126f303d0da7c4e48eec2004effd41d1b621193f17f9459e6

Observation 0b6bffd0-dac8-4212-ace4-2871341eb0e8 · outbound

This paper cites Con- nectionist temporal classification: labelling unsegmented se- quence data with recurrent neural networks,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Con- nectionist temporal classification: labelling unsegmented se- quence data with recurrent neural networks,

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:44.249157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:44.249157Z digest=sha256:2a270d9543007ca67e931d412fca37c809853f40290218ceaf82316c1110ba9c

Observation 4e72fc23-1160-4ee9-b1b5-a008c93ea0a4 · outbound

This paper cites Scalable diffusion models with transform- ers,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Scalable diffusion models with transform- ers,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.529971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.252601Z digest=sha256:5db4c8914d81fba53fc87bb90c4a04a8065228915cd0fbbcd98535f1fcd11a26

Observation 0adacf96-3d6a-4f60-a1f7-af1be2a10191 · outbound

This paper cites Classifier-free diffusion guidance,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Classifier-free diffusion guidance,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.516669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.256067Z digest=sha256:1ceea051f748ef9811232f951201d23544675cd0ba6561a1b4f56840126b4b1d

Observation ecfd3872-f8cb-489d-8213-21facddd9760 · outbound

This paper cites BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:44.260003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:44.260003Z digest=sha256:67faf22655583ac3a9cfefe820edfd36602ad7fb2073b3c01106d0b0799cc8af

Observation 94b5de5a-852e-49a6-85b2-644bcf701d94 · outbound

This paper cites L2-ARCTIC: A Non-native English Speech Corpus,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data L2-ARCTIC: A Non-native English Speech Corpus,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.502999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.264013Z digest=sha256:a24bca33d561b91e336aec11bd73c3aef6ec29b9ed5cd090c3c807e186ab1f54

Observation 7b0b4078-4262-407b-a87d-79539a1e670e · outbound

This paper cites The cmu arctic speech databases,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data The cmu arctic speech databases,

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:44.267499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:44.267499Z digest=sha256:55312cc4a9886218b8092de5fca1e0c0faeb4177dc2856686ab5942bc53b7280

Observation 104e2eee-112c-4e41-a0dd-99ee5bb95dd9 · outbound

This paper cites LibriTTS-R: A Restored Multi- Speaker Text-to-Speech Corpus,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data LibriTTS-R: A Restored Multi- Speaker Text-to-Speech Corpus,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.478485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.271356Z digest=sha256:282c6cefa83538589c83ba065fcfbf3948068f54c5cce787f1fba5eb6a12f2f4

Observation 02a47713-f3fc-4baa-bec3-3b3674e4d73f · outbound

This paper cites A comparison of best-worst scaling and rat- ing scale for timbre characterisation,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data A comparison of best-worst scaling and rat- ing scale for timbre characterisation,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.446484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.279511Z digest=sha256:a1dc3b1ebf448cd2783a8e170b996a1c83ae7d8e937e39516844cb8fdc7dbac8

Observation ad93342e-3a1a-44cc-9984-769c29c4149b · outbound

This paper cites Accented text- to-speech synthesis with limited data,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Accented text- to-speech synthesis with limited data,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.431990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.283851Z digest=sha256:db2cab2d8214c9f6f327428e17bdec9c66e88bd2881be2860ce1e0b71905cf0b

Observation edb3729a-033e-4092-b760-c0560e6bf426 · outbound

This paper cites High-fidelity neural phonetic posteriorgrams,.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data High-fidelity neural phonetic posteriorgrams,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.420760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.288042Z digest=sha256:7640063ca95eba9f6209db2bf2daf42df88e05df22a3c5e0cc4c4175616abc2f

Observation 686d8b5c-22fb-4a54-9f79-fd258e4ec75b · outbound

This paper cites For synthesis, we use flow matching [28] with Resemblyzer 5 speaker embeddings and BigVGAN [40] vocoding.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data For synthesis, we use flow matching [28] with Resemblyzer 5 speaker embeddings and BigVGAN [40] vocoding

Reference 1024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:44.956276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.097538Z digest=sha256:5849bc3180d127313b68be15e5587cd9e37d6aa128abc5c065b86880162d1288

Pith citing papers

Observation 56cec82a-4cef-4558-858a-aa341fa715e3 · inbound

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data cites this paper.

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-15T18:22:44.408368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T18:22:44.084075Z digest=sha256:69e00eb331385a003ae1e14607980bdf7d04e686a3879928a6132c02368a973d