Paper Citation Record · LEDGER

An Empirical Recipe for Universal Phone Recognition

As of 9 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 2 inbound Pith citation observations for arXiv:2603.29042.

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

pith.paper-citation-record.v1
2603.29042 v2

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T20:01:37.569548Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T20:01:37.569548Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:59:45.473466Z

Reference resolution

57 of 57 outbound references displayed

verified exact0
verified fuzzy0
unresolved55
parse uncertain0
malformed identifier2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5e3e4d15-2ed5-4b48-be69-1aeadf236891 · outbound

This paper cites PR is also heav- ily employed in atypical speech assessment [7, 8], computer- assisted language learning [9–11] and linguistic fieldwork [12– 14].

An Empirical Recipe for Universal Phone Recognition PR is also heav- ily employed in atypical speech assessment [7, 8], computer- assisted language learning [9–11] and linguistic fieldwork [12– 14]

Reference 1

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Unavailable: canonical work link unavailable.

Observation 4d827e40-68c4-4eec-8899-ff04ef42edf2 · outbound

This paper cites An Empirical Recipe for Universal Phone Recognition.

An Empirical Recipe for Universal Phone Recognition An Empirical Recipe for Universal Phone Recognition

Reference 2

Resolution: malformed identifier; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 7a26b9f5-882a-47ff-9454-0c3c00062bbd · outbound

This paper cites We evaluate the model with PRiSM [21], a benchmark for PR systems, and report the results in Table 1.

An Empirical Recipe for Universal Phone Recognition We evaluate the model with PRiSM [21], a benchmark for PR systems, and report the results in Table 1

Reference 3

Resolution: malformed identifier; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation cf4ec5b7-ff91-4ea7-b5d9-bcc1d3e4172d · outbound

This paper cites 2) MMS [45] (S3, S4), pretrained on 1k languages.

An Empirical Recipe for Universal Phone Recognition 2) MMS [45] (S3, S4), pretrained on 1k languages

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation fbfac1f3-5548-49a9-947f-71c7a8ec9060 · outbound

This paper cites We analyze the role of SSL in cross-lingual transfer via comparison with E-Branchformer (C5) which differs only in initialization to our recipe (C3).

An Empirical Recipe for Universal Phone Recognition We analyze the role of SSL in cross-lingual transfer via comparison with E-Branchformer (C5) which differs only in initialization to our recipe (C3)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08006426-522c-44c7-8b1c-c3d75feaed4f · outbound

This paper cites an unresolved cited work.

An Empirical Recipe for Universal Phone Recognition Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40a6a27c-3b84-4797-a7d5-8b6a7d50d185 · outbound

This paper cites All outputs were reviewed and validated by the authors.

An Empirical Recipe for Universal Phone Recognition All outputs were reviewed and validated by the authors

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cde200aa-9a29-4b6e-af81-f78b820cb78a · outbound

This paper cites The Zero Resource Speech Challenge 2019: TTS Without T,.

An Empirical Recipe for Universal Phone Recognition The Zero Resource Speech Challenge 2019: TTS Without T,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98cb50b9-0b5c-47a8-917f-ce0f41d639e7 · outbound

This paper cites The Zero Resource Speech Challenge 2021: Spoken Language Mod- elling,.

An Empirical Recipe for Universal Phone Recognition The Zero Resource Speech Challenge 2021: Spoken Language Mod- elling,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b77b322-c873-41da-93f7-354836801422 · outbound

This paper cites Self-supervised lan- guage learning from raw audio: Lessons from the zero resource speech challenge,.

An Empirical Recipe for Universal Phone Recognition Self-supervised lan- guage learning from raw audio: Lessons from the zero resource speech challenge,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed909d16-6421-49e8-851c-5e8174e9fae0 · outbound

This paper cites That Sounds Familiar: An Analysis of Phonetic Representations Transfer Across Lan- guages,.

An Empirical Recipe for Universal Phone Recognition That Sounds Familiar: An Analysis of Phonetic Representations Transfer Across Lan- guages,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f66df82a-d1cb-4cc3-bc4a-712c3f52409c · outbound

This paper cites Multilingual and crosslin- gual speech recognition using phonological-vector based phone embeddings,.

An Empirical Recipe for Universal Phone Recognition Multilingual and crosslin- gual speech recognition using phonological-vector based phone embeddings,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 3102040b-05a6-4f43-b2aa-4c02e4a9c4d3 · outbound

This paper cites Differentiable Allophone Graphs for Language-Universal Speech Recognition,.

An Empirical Recipe for Universal Phone Recognition Differentiable Allophone Graphs for Language-Universal Speech Recognition,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation fef92280-94fd-4f94-9424-34bf81d9619b · outbound

This paper cites Learner training for phonetic transcription of typical and/or disordered speech: A scoping review,.

An Empirical Recipe for Universal Phone Recognition Learner training for phonetic transcription of typical and/or disordered speech: A scoping review,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 319a771b-fd92-40d7-87bb-36fe0cbdca01 · outbound

This paper cites an unresolved cited work.

An Empirical Recipe for Universal Phone Recognition Unresolved cited work

Reference 15

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Observation f536f4ca-cdc9-4569-9475-4ef9eb585f35 · outbound

This paper cites Advances in phone-based modeling for automatic accent classification,.

An Empirical Recipe for Universal Phone Recognition Advances in phone-based modeling for automatic accent classification,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 1230ea7e-42f6-4be6-a27c-d4efb840656c · outbound

This paper cites EduSpeak®: A speech recognition and pronunciation scoring toolkit for computer-aided language learning applications,.

An Empirical Recipe for Universal Phone Recognition EduSpeak®: A speech recognition and pronunciation scoring toolkit for computer-aided language learning applications,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 4b312190-bded-4466-bdf5-c3f558d70db5 · outbound

This paper cites Automatic Pronuncia- tion Assessment-A Review,.

An Empirical Recipe for Universal Phone Recognition Automatic Pronuncia- tion Assessment-A Review,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 1c4ea5be-452a-4cf8-b6c6-055c523106c2 · outbound

This paper cites an unresolved cited work.

An Empirical Recipe for Universal Phone Recognition Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 2dd708de-a768-41e5-b91a-d9c1601b3c5d · outbound

This paper cites The UCLA Phonetics Lab Archive,.

An Empirical Recipe for Universal Phone Recognition The UCLA Phonetics Lab Archive,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation a59e2e89-70a5-4732-a28b-59c49c82a164 · outbound

This paper cites Tusom2021: A Phonetically Transcribed Speech Dataset from an Endangered Language for Universal Phone Recognition Experiments,.

An Empirical Recipe for Universal Phone Recognition Tusom2021: A Phonetically Transcribed Speech Dataset from an Endangered Language for Universal Phone Recognition Experiments,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation e987bf23-5325-4995-a9d3-7f2e9e32d968 · outbound

This paper cites Automatic recognition of phonetic patterns in speech,.

An Empirical Recipe for Universal Phone Recognition Automatic recognition of phonetic patterns in speech,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation a48396fc-2177-4c2e-b1e8-567ef2b81b3a · outbound

This paper cites Acoustic phonetic approach for speech recognition: A review,.

An Empirical Recipe for Universal Phone Recognition Acoustic phonetic approach for speech recognition: A review,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 9612e29a-00a5-4a4b-86b2-6391b93d3fea · outbound

This paper cites HuPER: A Human-Inspired Framework for Phonetic Perception,.

An Empirical Recipe for Universal Phone Recognition HuPER: A Human-Inspired Framework for Phonetic Perception,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 05b3cfc7-c000-4786-919c-1b63ea88a38d · outbound

This paper cites XLSR Inclusive English Speech-to-IPA,.

An Empirical Recipe for Universal Phone Recognition XLSR Inclusive English Speech-to-IPA,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb880130-0b75-4c17-8e4f-379cf7d41a79 · outbound

This paper cites ZIPA: A family of efficient models for multilingual phone recognition,.

An Empirical Recipe for Universal Phone Recognition ZIPA: A family of efficient models for multilingual phone recognition,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 9ff74116-b6ca-469a-8f39-e8099df60399 · outbound

This paper cites POWSM: A Phonetic Open Whisper-Style Speech Foundation Model,.

An Empirical Recipe for Universal Phone Recognition POWSM: A Phonetic Open Whisper-Style Speech Foundation Model,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9eab9d5-9e15-4646-a4b4-10712446601e · outbound

This paper cites PRiSM: Benchmarking Phone Realization in Speech Models.

An Empirical Recipe for Universal Phone Recognition PRiSM: Benchmarking Phone Realization in Speech Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0f8b766-afd1-4bc8-b2f2-298f9702f638 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

An Empirical Recipe for Universal Phone Recognition Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 6daa9862-0416-46d0-b0a1-ba732568f5c8 · outbound

This paper cites Qwen3-Omni Technical Report.

An Empirical Recipe for Universal Phone Recognition Qwen3-Omni Technical Report

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation d9698ef9-e626-4cde-8a28-1529787f8993 · outbound

This paper cites Simple and Effective Zero-shot Cross-lingual Phoneme Recognition,.

An Empirical Recipe for Universal Phone Recognition Simple and Effective Zero-shot Cross-lingual Phoneme Recognition,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 3e6f2be4-c394-4d7d-81f8-9fc3cda807e3 · outbound

This paper cites Universal Au- tomatic Phonetic Transcription into the International Phonetic Al- phabet,.

An Empirical Recipe for Universal Phone Recognition Universal Au- tomatic Phonetic Transcription into the International Phonetic Al- phabet,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 128ebd92-c589-418f-8046-e9ca89075dec · outbound

This paper cites Towards zero-shot learning for automatic phonemic transcrip- tion,.

An Empirical Recipe for Universal Phone Recognition Towards zero-shot learning for automatic phonemic transcrip- tion,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 590de913-f9d9-49bd-82eb-5479dab30dfb · outbound

This paper cites Universal phone recognition with a multilingual al- lophone system,.

An Empirical Recipe for Universal Phone Recognition Universal phone recognition with a multilingual al- lophone system,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 24cc05e6-3c61-490d-adad-6c73ba79d539 · outbound

This paper cites Allophant: Cross- lingual Phoneme Recognition with Articulatory Attributes,.

An Empirical Recipe for Universal Phone Recognition Allophant: Cross- lingual Phoneme Recognition with Articulatory Attributes,

Reference 35

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Observation 3508ec10-3a24-425a-99dd-2a1643470d49 · outbound

This paper cites The taste of IPA: Towards open-vocabulary keyword spotting and forced alignment in any language,.

An Empirical Recipe for Universal Phone Recognition The taste of IPA: Towards open-vocabulary keyword spotting and forced alignment in any language,

Reference 36

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Observation a6561630-6b90-4bf7-8325-ab6c277bfbce · outbound

This paper cites Multilingual Dysarthric Speech Assessment Using Universal Phone Recogni- tion and Language-Specific Phonemic Contrast Modeling,.

An Empirical Recipe for Universal Phone Recognition Multilingual Dysarthric Speech Assessment Using Universal Phone Recogni- tion and Language-Specific Phonemic Contrast Modeling,

Reference 37

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Observation 5c140f6e-6fde-4407-8807-61636485ce15 · outbound

This paper cites Towards robust speech representation learning for thousands of languages,.

An Empirical Recipe for Universal Phone Recognition Towards robust speech representation learning for thousands of languages,

Reference 38

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Observation 7492c43d-0ab2-4be0-9a79-ddfea792190b · outbound

This paper cites Layer-wise analysis of a self-supervised speech representation model,.

An Empirical Recipe for Universal Phone Recognition Layer-wise analysis of a self-supervised speech representation model,

Reference 39

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Observation 7e6c5455-f2a8-4c00-a4a6-9d9a29bfb127 · outbound

This paper cites Zipformer: A faster and better encoder for automatic speech recognition,.

An Empirical Recipe for Universal Phone Recognition Zipformer: A faster and better encoder for automatic speech recognition,

Reference 40

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Observation e151e11b-70ec-4d40-95ac-6f85b69153a1 · outbound

This paper cites CR-CTC: Consistency regularization on CTC for improved speech recognition,.

An Empirical Recipe for Universal Phone Recognition CR-CTC: Consistency regularization on CTC for improved speech recognition,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 38592093-7caa-4d83-a6df-1edef60dae46 · outbound

This paper cites Joint CTC-attention based end-to-end speech recognition using multi-task learning,.

An Empirical Recipe for Universal Phone Recognition Joint CTC-attention based end-to-end speech recognition using multi-task learning,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 5b48696c-967c-4831-b87d-7dfd9754eadc · outbound

This paper cites PanPhon: A Resource for Mapping IPA Segments to Articulatory Feature Vectors,.

An Empirical Recipe for Universal Phone Recognition PanPhon: A Resource for Mapping IPA Segments to Articulatory Feature Vectors,

Reference 43

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Observation 50a72b78-cde4-4917-9f4c-b01148fa10e8 · outbound

This paper cites Relaxing the Conditional Indepen- dence Assumption of CTC-Based ASR by Conditioning on Inter- mediate Predictions,.

An Empirical Recipe for Universal Phone Recognition Relaxing the Conditional Indepen- dence Assumption of CTC-Based ASR by Conditioning on Inter- mediate Predictions,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 02288618-6203-48e1-9e2d-f08aefa10f40 · outbound

This paper cites Connectionist temporal classification: labelling un- segmented sequence data with recurrent neural networks,.

An Empirical Recipe for Universal Phone Recognition Connectionist temporal classification: labelling un- segmented sequence data with recurrent neural networks,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation b6934bed-6b3f-4547-9ade-2d8cebe192df · outbound

This paper cites Hierarchical Multitask Learning With CTC,.

An Empirical Recipe for Universal Phone Recognition Hierarchical Multitask Learning With CTC,

Reference 46

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Observation c44816e8-8ce8-4db5-aba6-a48f93516f67 · outbound

This paper cites Intermediate loss regularization for ctc- based speech recognition,.

An Empirical Recipe for Universal Phone Recognition Intermediate loss regularization for ctc- based speech recognition,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 8ec224ea-dc8e-49a1-80fc-8766758bd88b · outbound

This paper cites Deja-vu: Double feature presen- tation and iterated loss in deep transformer networks,.

An Empirical Recipe for Universal Phone Recognition Deja-vu: Double feature presen- tation and iterated loss in deep transformer networks,

Reference 48

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 5e5f2907-d782-4665-9b3d-e00e2103dcae · outbound

This paper cites Im- proving massively multilingual asr with auxiliary ctc objectives,.

An Empirical Recipe for Universal Phone Recognition Im- proving massively multilingual asr with auxiliary ctc objectives,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 21e7fded-6a23-4dcd-af23-d5fd8f557eef · outbound

This paper cites Hierarchi- cal conditional end-to-end asr with ctc and multi-granular sub- word units,.

An Empirical Recipe for Universal Phone Recognition Hierarchi- cal conditional end-to-end asr with ctc and multi-granular sub- word units,

Reference 50

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Observation 058efa0e-b149-42b5-ba05-5526b96095a0 · outbound

This paper cites E-branchformer: Branchformer with enhanced merging for speech recognition,.

An Empirical Recipe for Universal Phone Recognition E-branchformer: Branchformer with enhanced merging for speech recognition,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation 6f998681-c4c3-453a-8cc8-0dfe22a696f1 · outbound

This paper cites Scaling Speech Technology to 1,000+ Lan- guages,.

An Empirical Recipe for Universal Phone Recognition Scaling Speech Technology to 1,000+ Lan- guages,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 51c510a3-7692-4c03-88e4-0d755d256a06 · outbound

This paper cites [b]=[d]-[t]+[p]: Self-supervised Speech Models Discover Phonological Vector Arithmetic.

An Empirical Recipe for Universal Phone Recognition [b]=[d]-[t]+[p]: Self-supervised Speech Models Discover Phonological Vector Arithmetic

Reference 53

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation dd7980a8-44d0-452a-b761-70d6c00aeafb · outbound

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

An Empirical Recipe for Universal Phone Recognition Hubert: Self-supervised speech represen- tation learning by masked prediction of hidden units,

Reference 54

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

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Observation c9a79db9-0f01-411d-9721-c96e53f6b80f · outbound

This paper cites Phonetic Seg- mentation of the UCLA Phonetics Lab Archive,.

An Empirical Recipe for Universal Phone Recognition Phonetic Seg- mentation of the UCLA Phonetics Lab Archive,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 28576cc6-9ee6-4fb3-b26d-49dbb099769e · outbound

This paper cites URIEL and lang2vec: Representing languages as typological, geographical, and phylogenetic vectors,.

An Empirical Recipe for Universal Phone Recognition URIEL and lang2vec: Representing languages as typological, geographical, and phylogenetic vectors,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Observation 7bef0f89-d439-4cde-aa89-6b422892d994 · outbound

This paper cites Speech Accent Archive,.

An Empirical Recipe for Universal Phone Recognition Speech Accent Archive,

Reference 57

Resolution: unresolved; no resolver link, observed 2026-07-14T20:01:37.569548Z

Source-reported events for the cited work

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Pith citing papers

Observation 4d827e40-68c4-4eec-8899-ff04ef42edf2 · inbound