Paper Citation Record · LEDGER

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet

As of 21 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 2 inbound Pith citation observations for arXiv:2508.16576.

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

pith.paper-citation-record.v1
2508.16576 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

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measured 50 of 50 standing notices

One-hop event checks from named stored sources.

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:16:31.102623Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T17:16:31.542417Z

Reference resolution

48 of 48 outbound references displayed

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External citation measurements

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Outbound references

Observation 2eafadc7-12b5-49dc-bbec-8791a94cbc41 · outbound

This paper cites Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet

Reference 1

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Observation 74fa6b2a-e06d-405b-88c5-1978a31ba304 · outbound

This paper cites fine-tuning), front-end representations, representation types (continuous vs.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet fine-tuning), front-end representations, representation types (continuous vs

Reference 2

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Observation 0994f503-58d8-4df7-a075-5efcf7235c8a · outbound

This paper cites Child speech corpora The experiments are conducted on three child speech corpora summarized in Table 1.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Child speech corpora The experiments are conducted on three child speech corpora summarized in Table 1

Reference 3

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Observation 6445c31f-81b7-4e2a-8b84-eeb5c398b3ae · outbound

This paper cites Flat-start training vs.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Flat-start training vs

Reference 4

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Observation 472239de-2e27-4c49-913c-fd43565cd75c · outbound

This paper cites While fine-tuned models generally perform best, flat-start models help mitigate biases in SSL representations, which are predominantly trained on adult speech.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet While fine-tuned models generally perform best, flat-start models help mitigate biases in SSL representations, which are predominantly trained on adult speech

Reference 5

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Observation 5dfb216a-0a63-428b-a632-db515e58a32a · outbound

This paper cites Additional support was provided by FWO-SBO grant S004923N: NEFL, KU Leuven C24M/22/025, and FWO grant V401325N.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Additional support was provided by FWO-SBO grant S004923N: NEFL, KU Leuven C24M/22/025, and FWO grant V401325N

Reference 6

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Observation 3ca39a5d-ac42-416b-bfb5-6d082c70b7a1 · outbound

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

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Wavlm: Large-scale self-supervised pre-training for full stack speech processing,

Reference 7

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Observation 1c608275-75bb-4a9b-b0da-6fd801d3376b · outbound

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

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Hubert: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:32.434279Z

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Observation 20aec226-25a8-42af-8994-e4e19a5732d3 · outbound

This paper cites Wav2vec 2.0: A framework for self-supervised learning of speech representations,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 9

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Observation df379917-991e-4840-9d00-441e59491b8a · outbound

This paper cites Robust speech recognition via large-scale weak supervision,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Robust speech recognition via large-scale weak supervision,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:32.368367Z

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Observation fad0f4ce-27fe-4651-be4f-58991921b337 · outbound

This paper cites Owsm v3.1: Better and faster open whisper-style speech models based on e-branchformer,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Owsm v3.1: Better and faster open whisper-style speech models based on e-branchformer,

Reference 11

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Observation fd70485c-8065-4542-b9d2-7cde717a2f52 · outbound

This paper cites Less is more: Accurate speech recognition & translation without web-scale data,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Less is more: Accurate speech recognition & translation without web-scale data,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:32.320551Z

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Observation 55526a59-4dda-47a1-b8a1-b5289fe3fc4e · outbound

This paper cites Acoustics of children’s speech: Developmental changes of temporal and spectral parameters,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Acoustics of children’s speech: Developmental changes of temporal and spectral parameters,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:32.302029Z

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Observation 2cba373b-c6f9-41d9-a4f4-66bdc9a0b23e · outbound

This paper cites On the difficulties of automatic speech recognition for kindergarten-aged children,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet On the difficulties of automatic speech recognition for kindergarten-aged children,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:32.282771Z

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Observation 721ca13b-b691-4858-bcae-c30ae3bae5dc · outbound

This paper cites Challenges remain in building ASR for sponta- neous preschool children speech in naturalistic educational envi- ronments,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Challenges remain in building ASR for sponta- neous preschool children speech in naturalistic educational envi- ronments,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:32.262963Z

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Observation 9b42ae76-4c44-480f-9976-8758c7177332 · outbound

This paper cites V ocal tract length perturbation (vtlp) improves speech recognition,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet V ocal tract length perturbation (vtlp) improves speech recognition,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:32.241891Z

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Observation c17c774b-058e-4795-aabb-e42dd1a2eee0 · outbound

This paper cites Prosodic adaptations to pitch perturbation in run- ning speech,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Prosodic adaptations to pitch perturbation in run- ning speech,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:32.223689Z

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Observation 6ad89029-9f22-40f4-a7a9-f5face5f7dee · outbound

This paper cites V oice Conversion Based Data Aug- mentation to Improve Children’s Speech Recognition in Limited Data Scenario,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet V oice Conversion Based Data Aug- mentation to Improve Children’s Speech Recognition in Limited Data Scenario,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:32.199171Z

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Observation d5cdc2ba-57ac-4600-b839-6d8372153ad2 · outbound

This paper cites Improved children’s automatic speech recognition combining adapters and synthetic data augmentation,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Improved children’s automatic speech recognition combining adapters and synthetic data augmentation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:32.176800Z

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Observation 7d53c064-1cad-4b49-aa08-d4c1440aa027 · outbound

This paper cites Transfer learning from adult to children for speech recognition: Evaluation, analysis and recommendations,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Transfer learning from adult to children for speech recognition: Evaluation, analysis and recommendations,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:32.150832Z

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Observation 594556bd-3869-4098-9d78-6f4021ce2dc6 · outbound

This paper cites Benchmarking children’s asr with supervised and self-supervised speech foundation models,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Benchmarking children’s asr with supervised and self-supervised speech foundation models,

Reference 21

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Observation 494033fe-5ea3-4c63-8eed-37988ad64a49 · outbound

This paper cites Kid-whisper: Towards bridging the per- formance gap in automatic speech recognition for children vs. adults,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Kid-whisper: Towards bridging the per- formance gap in automatic speech recognition for children vs. adults,

Reference 22

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This paper cites Ml-superb 2.0: Benchmarking multilingual speech models across modeling constraints, languages, and datasets,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Ml-superb 2.0: Benchmarking multilingual speech models across modeling constraints, languages, and datasets,

Reference 23

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Observation 3dbe124c-4e8c-42d6-89e8-63a6dad6700f · outbound

This paper cites On the evaluation of speech foundation models for spoken language understanding,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet On the evaluation of speech foundation models for spoken language understanding,

Reference 24

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Observation 773600a9-fd3d-4dbc-b007-063dc4c5e629 · outbound

This paper cites Speech self-supervised representations bench- marking: a case for larger probing heads,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Speech self-supervised representations bench- marking: a case for larger probing heads,

Reference 25

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Observation 2773c104-cbbb-4c8e-9750-de3cafca9114 · outbound

This paper cites Analysis of self-supervised speech models on chil- dren’s speech and infant vocalizations,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Analysis of self-supervised speech models on chil- dren’s speech and infant vocalizations,

Reference 26

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Observation 71112622-77f6-48da-ab32-6ecdba487a96 · outbound

This paper cites Towards better domain adaptation for self- supervised models: A case study of child asr,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Towards better domain adaptation for self- supervised models: A case study of child asr,

Reference 27

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Observation babb52d0-be38-4d49-9bd7-1f6dd553f87b · outbound

This paper cites Towards universal speech discrete tokens: A case study for ASR and TTS,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Towards universal speech discrete tokens: A case study for ASR and TTS,

Reference 28

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Observation b2ef6f22-7db0-4e07-be71-8765b62ee2b2 · outbound

This paper cites Exploration of efficient end-to-end ASR using discretized input from self-supervised learning,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Exploration of efficient end-to-end ASR using discretized input from self-supervised learning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.946700Z

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Observation 59c68ade-296d-41f4-b6f5-d309c9953c2a · outbound

This paper cites A wav2vec2-based experimental study on self- supervised learning methods to improve child speech recogni- tion,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet A wav2vec2-based experimental study on self- supervised learning methods to improve child speech recogni- tion,

Reference 30

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Observation 814d4849-537e-4311-b9f5-ad33a6eda4a0 · outbound

This paper cites Children’s speaker verification in low and zero resource conditions,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Children’s speaker verification in low and zero resource conditions,

Reference 31

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Observation 9afe58e0-cc83-44d8-97f7-1f37964f22d5 · outbound

This paper cites Childaugment: Data augmentation methods for zero-resource children’s speaker verification,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Childaugment: Data augmentation methods for zero-resource children’s speaker verification,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.874804Z

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Observation d68023b3-f0d8-4629-a5f3-126e7027ff36 · outbound

This paper cites Effective preservation of higher-frequency contents in the context of short utterance based children’s speaker verification system,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Effective preservation of higher-frequency contents in the context of short utterance based children’s speaker verification system,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.853967Z

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Observation cc235edc-9c73-4c81-b207-3b67131c1576 · outbound

This paper cites OWLS: Scaling Laws for Multilingual Speech Recognition and Translation Models.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet OWLS: Scaling Laws for Multilingual Speech Recognition and Translation Models

Reference 34

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This paper cites Espnet: End-to-end speech processing toolkit,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Espnet: End-to-end speech processing toolkit,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.830861Z

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Observation 038c33fa-bf1b-4ecc-a9c3-8b8dd4df821d · outbound

This paper cites Reproducing whisper-style training using an open- source toolkit and publicly available data,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Reproducing whisper-style training using an open- source toolkit and publicly available data,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.814241Z

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Observation f3a2d75d-323b-4ece-b301-ee4ddc39c05e · outbound

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

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Towards robust speech representation learning for thousands of languages,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.794888Z

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Observation fdd13e0a-4fac-41f3-9289-22fe6f801df7 · outbound

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

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet E-branchformer: Branchformer with enhanced merging for speech recognition,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.770338Z

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Observation fef85494-3100-4877-bc37-33968fc7e3c4 · outbound

This paper cites A comparative study on transformer vs rnn in speech applications,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet A comparative study on transformer vs rnn in speech applications,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.751586Z

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Observation f4f9e820-4f9d-41b2-bcd4-c69025630516 · outbound

This paper cites Sequence Transduction with Recurrent Neural Networks.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Sequence Transduction with Recurrent Neural Networks

Reference 40

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Observation a504f094-8293-4cc0-9994-55f1f8bdb81f · outbound

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

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.729544Z

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Observation 2a22ccac-1f5b-4b56-9a34-a33a7698790c · outbound

This paper cites OWSM-CTC: An open encoder-only speech foun- dation model for speech recognition, translation, and language identification,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet OWSM-CTC: An open encoder-only speech foun- dation model for speech recognition, translation, and language identification,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.706898Z

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Observation c7b93c42-67f5-47c6-9344-4757ecb539f5 · outbound

This paper cites Pushing the limits of raw waveform speaker recognition,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Pushing the limits of raw waveform speaker recognition,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.687511Z

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Observation b7adcdf7-cbfd-48eb-9ea0-cf29b959cac9 · outbound

This paper cites Espnet-spk: full pipeline speaker embedding toolkit with reproducible recipes, self-supervised front-ends, and off-the-shelf models,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Espnet-spk: full pipeline speaker embedding toolkit with reproducible recipes, self-supervised front-ends, and off-the-shelf models,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.666598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6a918204-7ae3-4e31-8952-583a8af7f7de · outbound

This paper cites My science tutor (MyST)–a large corpus of children‘s conversational speech,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet My science tutor (MyST)–a large corpus of children‘s conversational speech,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.644503Z

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Observation 7e1175c4-7c7b-4688-ab3e-64f4d69acd9a · outbound

This paper cites The ogi kids’ speech corpus and recognizers,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet The ogi kids’ speech corpus and recognizers,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.625739Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ad1048c3-6eca-4cb5-80ea-0d2c0ed7bdc3 · outbound

This paper cites The cmu kids corpus,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet The cmu kids corpus,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.605906Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ccb227d1-072e-48b1-97f8-8f76f5dd4358 · outbound

This paper cites Superb: Speech processing universal perfor- mance benchmark,.

Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet Superb: Speech processing universal perfor- mance benchmark,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:16:31.582622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation 2eafadc7-12b5-49dc-bbec-8791a94cbc41 · inbound