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Paper Citation Record · LEDGER

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition

As of 17 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 1 inbound Pith citation observation for arXiv:2603.09725.

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

pith.paper-citation-record.v1
2603.09725 v2

Coverage vector

measured 79 of 79 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-15T00:03:31.986628Z

measured 80 of 80 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-15T00:03:31.986628Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

79 of 79 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved77
  • parse uncertain0
  • malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 317e5a3c-dbf6-48ab-9638-64ce0c1bf34c · outbound

This paper cites A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition

Reference 1

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Observation ba5d15b3-aef7-4985-8e52-a491befb5c07 · outbound

This paper cites Corpus design To elicit spontaneous speech and to ensure both lexical and pho- netic diversity, three tasks were designed:.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Corpus design To elicit spontaneous speech and to ensure both lexical and pho- netic diversity, three tasks were designed:

Reference 2

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Observation 72a419ba-0bdd-46af-a3ba-3c927777c90c · outbound

This paper cites an unresolved cited work.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Unresolved cited work

Reference 3

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Observation 9faa78e0-2fce-4dca-80bb-56a4776bcde4 · outbound

This paper cites an unresolved cited work.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Unresolved cited work

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Observation 357e4394-faf0-40c6-97ba-2096347577fb · outbound

This paper cites Tell something about [topic 1] or [topic 2].

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Tell something about [topic 1] or [topic 2]

Reference 5

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Observation 1611fa21-ac46-4f85-aa01-1d06bb87e1e0 · outbound

This paper cites The speech quality is particularly low for the recordings made at location Ahoy, highlighting the difficult acoustic conditions.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition The speech quality is particularly low for the recordings made at location Ahoy, highlighting the difficult acoustic conditions

Reference 6

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Observation bd07b743-8d18-4550-8f67-82a5b456d51a · outbound

This paper cites Noisereduce.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Noisereduce

Reference 7

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Observation 0615c3ff-73fa-4054-a654-f17c8cd750b9 · outbound

This paper cites Base” is identical to “Overall.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Base” is identical to “Overall

Reference 8

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Observation 07d61981-ab98-4a9c-a687-bc3fdc00165e · outbound

This paper cites We evaluated several SOTA ASR models on speech from DRES and evaluated the effect of several classical and modern single-channel speech enhancement (SE) al- gorithms.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition We evaluated several SOTA ASR models on speech from DRES and evaluated the effect of several classical and modern single-channel speech enhancement (SE) al- gorithms

Reference 9

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Observation 006bbaa3-7e46-4b75-99eb-dab5ec343b02 · outbound

This paper cites an unresolved cited work.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Unresolved cited work

Reference 10

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Observation b928f33b-7273-4d0b-93e6-67f9bb20d8d1 · outbound

This paper cites After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication

Reference 11

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Observation 5d1cd31e-f6cc-4090-b971-f385183d312f · outbound

This paper cites Development of speech recognition systems in emergency call centers,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Development of speech recognition systems in emergency call centers,

Reference 12

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Observation ed631508-4e27-4728-b958-b0ee876c1c25 · outbound

This paper cites A systematic review of speech recognition technology in health care,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition A systematic review of speech recognition technology in health care,

Reference 13

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Observation a6a0c383-cd08-4b57-bf74-5a5c3753ca3c · outbound

This paper cites Evaluating automatic speech recognition-based language learning systems: A case study,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Evaluating automatic speech recognition-based language learning systems: A case study,

Reference 14

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Observation 851d034f-7956-4025-826a-3e5a00f91d12 · outbound

This paper cites Investigating RNN-based speech enhancement methods for noise- robust Text-to-Speech,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Investigating RNN-based speech enhancement methods for noise- robust Text-to-Speech,

Reference 15

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Observation 337c63bd-3142-48c7-a588-c6c815f60bc8 · outbound

This paper cites Subjective evaluation and comparison of speech enhance- ment algorithms,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Subjective evaluation and comparison of speech enhance- ment algorithms,

Reference 16

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Observation 39a5a0ff-5017-4113-87b7-c42483c65818 · outbound

This paper cites EARS: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberation,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition EARS: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberation,

Reference 17

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Observation c054668e-338b-4a24-8921-bf3b622b7cc3 · outbound

This paper cites The AURORA experimental frame- work for the performance evaluation of speech recognition systems under noisy conditions,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition The AURORA experimental frame- work for the performance evaluation of speech recognition systems under noisy conditions,

Reference 18

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Observation 665d7a7e-ff0a-497d-9357-99174c6b50a6 · outbound

This paper cites The PASCAL CHiME speech separation and recognition challenge,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition The PASCAL CHiME speech separation and recognition challenge,

Reference 19

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Observation ebfe3f68-f499-4978-a55a-e78fa8223492 · outbound

This paper cites The HIWIRE database, a noisy and non- native English speech corpus for cockpit communication,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition The HIWIRE database, a noisy and non- native English speech corpus for cockpit communication,

Reference 20

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Observation 5ba469fe-ae8a-4349-a38d-89692d07e5f8 · outbound

This paper cites The evolution of the lombard effect: 100 years of psychoacoustic research,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition The evolution of the lombard effect: 100 years of psychoacoustic research,

Reference 21

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Observation d88a0eba-f4e6-49eb-96b5-42adaf8efbaf · outbound

This paper cites The lombard effect: a reflex to better communicate with others in noise,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition The lombard effect: a reflex to better communicate with others in noise,

Reference 22

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Observation 652ae347-7f7e-4f92-b678-78db27ae59f5 · outbound

This paper cites Speech production modifications produced by competing talkers, babble, and stationary noise,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Speech production modifications produced by competing talkers, babble, and stationary noise,

Reference 23

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Observation e8cdf3ad-c287-444f-9823-64376aeae7ef · outbound

This paper cites Influence of Sound Im- mersion and Communicative Interaction on the Lombard Effect,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Influence of Sound Im- mersion and Communicative Interaction on the Lombard Effect,

Reference 24

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Observation 3ef7d138-69b2-4a93-865a-7905a793ca10 · outbound

This paper cites Under- standing Lombard speech: a review of compensation techniques towards improving speech based recognition systems,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Under- standing Lombard speech: a review of compensation techniques towards improving speech based recognition systems,

Reference 25

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Observation 4aa23123-2e15-4afa-8df4-c21f1b65b06a · outbound

This paper cites The third ‘chime’speech separation and recognition challenge: Dataset, task and baselines,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition The third ‘chime’speech separation and recognition challenge: Dataset, task and baselines,

Reference 26

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Observation ee961885-1a5c-4d9f-a015-55cf740206bb · outbound

This paper cites MISP-meeting: A real-world dataset with multimodal cues for long-form meeting transcription and summarization,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition MISP-meeting: A real-world dataset with multimodal cues for long-form meeting transcription and summarization,

Reference 27

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Observation 7bae8623-5382-451e-a5ac-ad906a013429 · outbound

This paper cites One-pass single-channel noisy speech recognition using a combination of noisy and enhanced features,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition One-pass single-channel noisy speech recognition using a combination of noisy and enhanced features,

Reference 28

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Observation 93afb14a-496c-4d55-81d3-59424f5c1389 · outbound

This paper cites How bad are artifacts?: Analyzing the impact of speech enhancement errors on ASR,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition How bad are artifacts?: Analyzing the impact of speech enhancement errors on ASR,

Reference 29

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Observation 37930064-b7b7-4f3e-8ecf-14eaac642e2d · outbound

This paper cites Noise robust automatic speech recognition: review and analysis,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Noise robust automatic speech recognition: review and analysis,

Reference 30

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Observation 81774b6a-3783-44be-82d9-61512842a834 · outbound

This paper cites The Spoken Dutch Corpus. Overview and first evalu- ation,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition The Spoken Dutch Corpus. Overview and first evalu- ation,

Reference 31

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Observation 9cbad575-d860-46b4-a5aa-1e3211ae69ab · outbound

This paper cites JASMIN-CGN: Extension of the spoken Dutch corpus with speech of elderly people, children and non-natives in the human-machine interaction modality,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition JASMIN-CGN: Extension of the spoken Dutch corpus with speech of elderly people, children and non-natives in the human-machine interaction modality,

Reference 32

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Observation 5524b788-b888-421a-b675-65cc93c9bf0e · outbound

This paper cites Common Voice: A Massively-Multilingual Speech Corpus.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Common Voice: A Massively-Multilingual Speech Corpus

Reference 33

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Observation 4eab928b-dc0d-40e1-8a54-1cf5dbbfe9b8 · outbound

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

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Robust speech recognition via large-scale weak super- vision,

Reference 34

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Observation 5ff29283-ed42-419e-b5a4-46b040287249 · outbound

This paper cites Uncovering bias in asr systems: Evaluating wav2vec2 and whisper for dutch speakers,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Uncovering bias in asr systems: Evaluating wav2vec2 and whisper for dutch speakers,

Reference 35

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Observation 97296e55-856c-4efd-a0d6-eea8f452de14 · outbound

This paper cites Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data

Reference 36

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Observation e50d8560-61f3-4cca-9896-0628d83d7eca · outbound

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

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 37

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Observation 88ce15bb-e1c1-4df0-ac00-8465a02455ae · outbound

This paper cites To- wards inclusive automatic speech recognition,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition To- wards inclusive automatic speech recognition,

Reference 38

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Observation 28af6dfc-fdeb-403b-a4aa-f7575db52074 · outbound

This paper cites Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages

Reference 39

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Observation 1d712606-debe-4329-add8-9720ab45fcb1 · outbound

This paper cites Speech-to-text overview,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Speech-to-text overview,

Reference 40

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Observation c2140d99-4410-43ee-9804-3f556bdb1c5b · outbound

This paper cites Scaling speech technology to 1,000+ languages,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Scaling speech technology to 1,000+ languages,

Reference 41

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Observation d98436ca-aec6-4a2e-a824-65e45e12b7f3 · outbound

This paper cites stt nl fastconformer hybrid large pc,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition stt nl fastconformer hybrid large pc,

Reference 42

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:31dfd6754efbd228dbe370b235c3f80b44ed8a230413306c4bf52489273f5418

Observation ff583e43-91f7-4b38-8f6a-3e91447105e1 · outbound

This paper cites A new standard for speech recognition and translation from the NVIDIA nemo canary model,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition A new standard for speech recognition and translation from the NVIDIA nemo canary model,

Reference 43

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:88640b421a23a06a5da3a8c65dd31eeae0adee0f8aaaded67579bc26d1968851

Observation b70c9398-c1e2-4bc3-9046-1faea3746046 · outbound

This paper cites YuanyuanZhang/DutchCGNConformerFBank: ES- Pnet2 ASR model,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition YuanyuanZhang/DutchCGNConformerFBank: ES- Pnet2 ASR model,

Reference 44

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:66afb2d59fd25790c0565eb1a375f64604ba6a168e9c7e7afd1566f855c3dbe4

Observation 81262e51-57dc-41ff-8fcd-e7c5f39793e1 · outbound

This paper cites Far-field automatic speech recognition,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Far-field automatic speech recognition,

Reference 45

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:c34619e0f44ec8bb385d6b08fd93014c9dae682d80065ecd0bc811483c0156e8

Observation f38d056f-bab3-476d-bd15-7e1e1aef59db · outbound

This paper cites Advances in microphone array processing and multichannel speech enhancement,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Advances in microphone array processing and multichannel speech enhancement,

Reference 46

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:545af0c3d3bcc3de954252efc0e337c64b24f1e92cade8e5e4ff9c8517264591

Observation 2f59748d-cb6d-40c3-afbe-114a281298b0 · outbound

This paper cites Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups,

Reference 47

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:41dca7c5ee833c22bcbebd0e8b723a8d07e65c9a426e17b3d75378756c639db7

Observation a0150aec-95b5-4973-8995-39722def2a13 · outbound

This paper cites Bridging the gap between monaural speech enhancement and recognition with distortion- independent acoustic modeling,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Bridging the gap between monaural speech enhancement and recognition with distortion- independent acoustic modeling,

Reference 48

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:429ab17fe97a9aece513298c4a5ccbd624ad4869b13a2cdc0db4bf49c3563a4a

Observation 418be293-d103-4641-8e91-9d1576647554 · outbound

This paper cites NAaLOSS: Re- thinking the Objective of Speech Enhancement,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition NAaLOSS: Re- thinking the Objective of Speech Enhancement,

Reference 49

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:441d788c970ba292eae6f409481babaaff129e7822e1d3f3f622e8cc67ed620a

Observation 415c2288-a89b-4930-9291-862f62cad652 · outbound

This paper cites Speech enhancement and dereverberation with diffusion-based generative models,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Speech enhancement and dereverberation with diffusion-based generative models,

Reference 50

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:7fa60b64bab3606ae807fdd26ace83841488ae2b5a953ad415366e7528d3c708

Observation 0879d4eb-7cff-4b1d-92d5-e0d759c3ab49 · outbound

This paper cites StoRM: A Diffusion-Based Stochastic Regeneration Model for Speech En- hancement and Dereverberation,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition StoRM: A Diffusion-Based Stochastic Regeneration Model for Speech En- hancement and Dereverberation,

Reference 51

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:74cedbc76ca7cf6ad257a258c5b46da766660c05b6d27e6d98ff6514d0911a0b

Observation 1e9b5236-2a2a-4bd7-b95b-f9563fe3c78d · outbound

This paper cites Latent-level enhancement with flow matching for robust automatic speech recognition,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Latent-level enhancement with flow matching for robust automatic speech recognition,

Reference 52

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:f7e5d5a67b6f918f4dc48f11548c1b7798f249af62034d3400290fbbb1030d04

Observation d2bad352-e031-4c16-a359-685f58e4cc1d · outbound

This paper cites Evaluating speech enhancement performance across demographics and language,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Evaluating speech enhancement performance across demographics and language,

Reference 53

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:ccc0ef155b7fb0a26e171fcb712d94338db1dd2e790758b8ada41fe322def819

Observation a0c50c42-0b81-4f38-a4bd-3bc0c3dc740d · outbound

This paper cites Enhancement of speech corrupted by acoustic noise,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Enhancement of speech corrupted by acoustic noise,

Reference 54

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:5c767a85b8dc65580faa3aedb48a5fc68e2c592cff6634ec17ffff7a2e21e8a7

Observation ebb8dc2f-cb8a-4d35-8ede-99aaeda0ecb5 · outbound

This paper cites Finding, visualizing, and quantifying latent structure across diverse animal vocal reper- toires,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Finding, visualizing, and quantifying latent structure across diverse animal vocal reper- toires,

Reference 55

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:c7d5e53b6d63e0e9f6b9e1a0158ca4e768843e6b6222d7198562f2b03dd42d1f

Observation aaef90c4-bc32-4af2-a8d9-0d9b051226f2 · outbound

This paper cites MetricGAN-OKD: Multi-metric optimization of MetricGAN via online knowledge distillation for speech enhancement,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition MetricGAN-OKD: Multi-metric optimization of MetricGAN via online knowledge distillation for speech enhancement,

Reference 56

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:ab2796d91291cc188f72f99c86e2c4616808b4b8ff9afc9583e87592fc41d345

Observation d7b72fc5-fd78-4ea8-99fc-193a018b7abb · outbound

This paper cites [Online].

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition [Online]

Reference 57

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:191c327a3ca4a45fc164216ae6c4818c2bdc7b6185c24d1e9312caf362515ae8

Observation 44a9ef58-fc02-416c-bcd4-f3e540147fff · outbound

This paper cites Dnsmos p.835: A non- intrusive perceptual objective speech quality metric to evaluate noise suppressors,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Dnsmos p.835: A non- intrusive perceptual objective speech quality metric to evaluate noise suppressors,

Reference 58

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:faea3c5527a129f2b410b06b0adadee37a908b6874d250f2adce2130434810c6

Observation 603f6438-a9a0-41c3-acfc-b697ce0498ed · outbound

This paper cites Suppression of acoustic noise in speech using spectral subtraction,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Suppression of acoustic noise in speech using spectral subtraction,

Reference 59

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:e22239dbffaa5bd8d2f4e227c2985292847c4df2ecfb3f01c7f7cd9db2b63757

Observation cecf1ab2-aea4-46b7-9beb-00618972669a · outbound

This paper cites Speech enhancement—a review of modern methods,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Speech enhancement—a review of modern methods,

Reference 60

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:be3e8edc6cd71b80433f00e2a54a9b66ab9c8ea108659981203cc8cca7df1afd

Observation 4a4f140f-bfd2-4332-a9c9-086a388576a9 · outbound

This paper cites A perceptual masking approach for noise robust speech recognition,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition A perceptual masking approach for noise robust speech recognition,

Reference 61

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:87afbaa93c0c117f9788ce448ed2d5c8ef5ccd690a3bc2fb1c6a20b1bb523aa3

Observation 721ce7c3-bfd7-4bc1-b1a5-b2a7ed638354 · outbound

This paper cites Pyroomacoustics: A python package for audio room simulation and array processing al- gorithms,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Pyroomacoustics: A python package for audio room simulation and array processing al- gorithms,

Reference 62

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:a58504f6be12fd9de572e69bd311afe0b0b1d4be7271420bdc3221c33e42e68c

Observation 65fa08b2-319c-4858-a10a-f0e41ce3b0b2 · outbound

This paper cites Toward a computational neu- roethology of vocal communication: From bioacoustics to neu- rophysiology, emerging tools and future directions,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Toward a computational neu- roethology of vocal communication: From bioacoustics to neu- rophysiology, emerging tools and future directions,

Reference 63

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:7a872dc968ddf69087634fcbb20365c01395a5e1f826ef13959e441fe31368a7

Observation 272d2463-344c-40e9-9638-2510a74bc1da · outbound

This paper cites Domain general noise reduction for time series signals with noisereduce,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Domain general noise reduction for time series signals with noisereduce,

Reference 64

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:06226214d11aef345a9d5548367b67ee61f161f35727cbae81f93813ff646006

Observation 517e879e-ce44-43f5-a7ae-daad627dad09 · outbound

This paper cites Objective and subjective evaluation of diffusion-based speech en- hancement for dysarthric speech,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Objective and subjective evaluation of diffusion-based speech en- hancement for dysarthric speech,

Reference 65

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Observation 4b081909-9075-4b58-bc38-bf6e88b7ce51 · outbound

This paper cites timsainb/noisereduce: 3.0.3,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition timsainb/noisereduce: 3.0.3,

Reference 66

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:2fd45c3e0a0261de9205c1576850b13c36c3672a9e11220738a25e0afab2f629

Observation 9cdbaca7-dbda-4626-8bf5-84ad1203fd5e · outbound

This paper cites Speech Enhancement and Dereverberation with Diffusion-based Generative Models,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Speech Enhancement and Dereverberation with Diffusion-based Generative Models,

Reference 67

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Observation 12254d3f-b326-4fde-a4dc-f2391ff75f19 · outbound

This paper cites Available: https://github.com/sp-uhh/sgmse.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Available: https://github.com/sp-uhh/sgmse

Reference 68

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:c53182feb0bcbc77fda7733a56ff16460b78e8b2c13a625c53f6790c1b81c580

Observation c90a0cdb-b147-4fdd-b93e-f7e724acd030 · outbound

This paper cites Speech-to-text: Transcription models,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Speech-to-text: Transcription models,

Reference 69

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:6ce465a1189711369cdf45ef5cd128ebc06cce8695da3bd5ab692df7586d334e

Observation 75a00d89-4ec5-4859-9ad1-11f70cfce25a · outbound

This paper cites facebook/mms-1b-all: Massively Multilingual Speech (MMS),.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition facebook/mms-1b-all: Massively Multilingual Speech (MMS),

Reference 70

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:94d677c0fdfedbe15d1de40944aec86f79614c4315e790bb6fa14428c5d7d224

Observation c91a1f32-a497-4aac-b176-294a17d9e819 · outbound

This paper cites Whisper-large-v3,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Whisper-large-v3,

Reference 71

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:f93844309ebe90a72f6aa7c9abbec90f79649982c50a7bdd05dbe361be0f7594

Observation a359ee39-045e-4391-90ac-d2c9dfef6e8f · outbound

This paper cites FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech

Reference 72

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:0890e01c2ca7c870f6d6bc95c9593a4811c827b40d9ae427efdb60c0f564accf

Observation 229d74a4-7bfb-48bb-96a4-36303bca0b1a · outbound

This paper cites Whisper github discussion #2363,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Whisper github discussion #2363,

Reference 73

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source=pdf_text observed=2026-07-15T00:03:31.986628Z digest=sha256:b789dc1e52c34331f34ed585c7847601d56a501db8e4668d5b3465aa3d852555

Observation 9d48ce60-ab4c-40e0-a1bd-cae808881401 · outbound

This paper cites MLS: A Large-Scale Multilingual Dataset for Speech Research.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition MLS: A Large-Scale Multilingual Dataset for Speech Research

Reference 74

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Observation 21093ffe-41f4-445d-8d76-c11f59339e69 · outbound

This paper cites VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation

Reference 75

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Observation 33c39fe1-efad-4c5d-a41e-9b5fbceb4ce8 · outbound

This paper cites Bootstrap estimates for confidence intervals in asr performance evaluation,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Bootstrap estimates for confidence intervals in asr performance evaluation,

Reference 76

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Observation 61db57a4-e31f-47e7-8b9d-9aa1840eab81 · outbound

This paper cites Good practices for evaluation of machine learning systems.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Good practices for evaluation of machine learning systems

Reference 77

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Observation d7f257d5-4b9f-471f-9587-fb9224f00a14 · outbound

This paper cites an unresolved cited work.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Unresolved cited work

Reference 78

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Observation 9b0159b5-4b30-4fac-bceb-474f34c9d575 · outbound

This paper cites ITU-T Recommenda- tion P.835: Subjective test methodology for evaluating speech communication systems that include noise suppression algorithm,.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition ITU-T Recommenda- tion P.835: Subjective test methodology for evaluating speech communication systems that include noise suppression algorithm,

Reference 79

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Pith citing papers

Observation 317e5a3c-dbf6-48ab-9638-64ce0c1bf34c · inbound

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition cites this paper.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition

Reference 1

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