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Paper Citation Record · LEDGER

Probabilistic Permutation Invariant Training for Speech Separation

As of 16 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:1908.01768.

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

pith.paper-citation-record.v1
1908.01768 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:20:29.682290Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:20:29.404068Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T15:20:29.807585Z

Reference resolution

44 of 44 outbound references displayed

  • verified exact2
  • verified fuzzy32
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d1c30595-5684-40ec-a014-01b2e4bf24a7 · outbound

This paper cites Probabilistic Permutation Invariant Training for Speech Separation.

Probabilistic Permutation Invariant Training for Speech Separation Probabilistic Permutation Invariant Training for Speech Separation

Reference 1

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metadata mismatch
local_arxiv, observed 2026-08-14T15:20:29.813178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.404068Z digest=sha256:573eef69bfcb9fc497d2ec1f1864d0bf425927347667dfa31f65035f97952600

Observation bfc0692d-5982-40b1-8c5d-11d9219fde1f · outbound

This paper cites an unresolved cited work.

Probabilistic Permutation Invariant Training for Speech Separation Unresolved cited work

Reference 2

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unresolved
raw_fallback, observed 2026-08-14T15:20:30.576370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.411690Z digest=sha256:10d4c0e996581252099822ec69c3dad172d8998d7b4b79ba350d56c394a56027

Observation c8a70b1e-a63b-46f0-b140-ff95de14e690 · outbound

This paper cites an unresolved cited work.

Probabilistic Permutation Invariant Training for Speech Separation Unresolved cited work

Reference 3

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unresolved
raw_fallback, observed 2026-08-14T15:20:30.559327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.419220Z digest=sha256:78f3c9bd96dab03a0d849dd911731f29bd12faec1e620a96fcef5ec712aa58d7

Observation baf4854f-e975-49bc-8cbc-02b03060db0b · outbound

This paper cites The GRID is a multi-speaker, sentence corpus [32], which has been used in monaural speech separation and recogni- tion challenge [33].

Probabilistic Permutation Invariant Training for Speech Separation The GRID is a multi-speaker, sentence corpus [32], which has been used in monaural speech separation and recogni- tion challenge [33]

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.541884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.425569Z digest=sha256:9248d0b397605d5e9ea3d62661f372b6f084651e1d7d25a65479e4ff5f400eb3

Observation 7ad0ed54-4dd7-4b5c-9a80-672a9535e412 · outbound

This paper cites A long-lasting problem in speech separation task is finding the correct label for each separated speech signal, which referred to as label permutation ambiguity.

Probabilistic Permutation Invariant Training for Speech Separation A long-lasting problem in speech separation task is finding the correct label for each separated speech signal, which referred to as label permutation ambiguity

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.525144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.431108Z digest=sha256:15b195d727aa9caf33ab3034d43ca3cf9a7d627bf813728a878c6316c62adb2d

Observation 8445e94c-3d4d-4a9f-9319-b7a35c1ce453 · outbound

This paper cites The perception of speech under adverse conditions,.

Probabilistic Permutation Invariant Training for Speech Separation The perception of speech under adverse conditions,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.507734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.436689Z digest=sha256:2a10f75ff19dcc95205c2a88dd6f90bfe713ffa597dc75987ce34419df6042b5

Observation b8dbc153-ab9c-420f-a44d-d4695e866a58 · outbound

This paper cites an unresolved cited work.

Probabilistic Permutation Invariant Training for Speech Separation Unresolved cited work

Reference 7

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unresolved
raw_fallback, observed 2026-08-14T15:20:30.491135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.443118Z digest=sha256:ebaf8fb878919d9e197cb3cf4a5894f4dd1aa5bc6f06da55447bb9d929027ac1

Observation a78bf3ce-abe4-46fb-ae59-e42e3c28b937 · outbound

This paper cites Auditory grouping, i in hearing. hand- book of perception and cognition, bcj moore,.

Probabilistic Permutation Invariant Training for Speech Separation Auditory grouping, i in hearing. hand- book of perception and cognition, bcj moore,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.472709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.448977Z digest=sha256:ea5ea1472e9ca3153a3541c3048b0c5b8b36c83d19ca7f23d83bff7b2eab9388

Observation 76745c39-867f-48d4-8424-b78a7472ae8f · outbound

This paper cites Divenyi, Speech separation by humans and machines.

Probabilistic Permutation Invariant Training for Speech Separation Divenyi, Speech separation by humans and machines

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.455517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.455920Z digest=sha256:7e4798f27e3d29db79dcca3c340371fcc7b7d070591b9eb15567f2880e3d8aac

Observation f7e83704-b4c1-40e7-820f-7067cdde5b2d · outbound

This paper cites An algorithm to increase intelligibility for hearing-impaired lis- teners in the presence of a competing talker,.

Probabilistic Permutation Invariant Training for Speech Separation An algorithm to increase intelligibility for hearing-impaired lis- teners in the presence of a competing talker,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.437200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.462747Z digest=sha256:296b28f9b2b0b52c1bec4b1db75de3b9877c85fecf54ac590e45372370a6007f

Observation 484a3842-426d-40f8-8d0f-2b19b935788d · outbound

This paper cites Eeg-informed attended speaker extraction from recorded speech mixtures with application in neuro-steered hearing prostheses,.

Probabilistic Permutation Invariant Training for Speech Separation Eeg-informed attended speaker extraction from recorded speech mixtures with application in neuro-steered hearing prostheses,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.418056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.470796Z digest=sha256:cce30460b562844c7fc9cc9d2c90bb15c34f2f81244d06ed74aa5015e9936682

Observation 2d41bb52-2a1b-438f-85a1-a5377b5aa9d4 · outbound

This paper cites Deep recurrent networks for separation and recognition of single- channel speech in nonstationary background audio,.

Probabilistic Permutation Invariant Training for Speech Separation Deep recurrent networks for separation and recognition of single- channel speech in nonstationary background audio,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.395428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.477340Z digest=sha256:4ff9f783a26cbc2619c6ec89ed6da593ac91fd1c68c9f51f0d84e51cfdb48ca1

Observation 73f9fe41-78af-4683-84a8-17b0f23a54a2 · outbound

This paper cites Single-channel mul- titalker speech recognition,.

Probabilistic Permutation Invariant Training for Speech Separation Single-channel mul- titalker speech recognition,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.376541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.483440Z digest=sha256:22efc1b3134ea73943e19caac532c642823c9d617496923c5718c48ff9153715

Observation dbb523bd-e7da-466b-a6e5-c076b0c8ab74 · outbound

This paper cites Deep neu- ral networks for single-channel multi-talker speech recognition,.

Probabilistic Permutation Invariant Training for Speech Separation Deep neu- ral networks for single-channel multi-talker speech recognition,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.354799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.488886Z digest=sha256:01cc85752858f6e279cc8bf503aa05b6ee02742a3c7eb04023fb7bff463f0a98

Observation 9916df4f-2de8-463e-9b42-f037bd7cdc62 · outbound

This paper cites Multi-speaker conversations, cross-talk, and diarization for speaker recognition,.

Probabilistic Permutation Invariant Training for Speech Separation Multi-speaker conversations, cross-talk, and diarization for speaker recognition,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.325342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.495505Z digest=sha256:dfdcb6d5d4e25092927fa0e171c3345ba7a0a1e3eb91d1037ea1279536a652a3

Observation 4c3e0e54-347c-41dd-861b-933720ac4a4b · outbound

This paper cites All-neural online source separation, counting, and diarization for meeting analysis.

Probabilistic Permutation Invariant Training for Speech Separation All-neural online source separation, counting, and diarization for meeting analysis

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-08-14T15:20:29.787083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.501091Z digest=sha256:537199cfca3d21c3328c37ee3f1696bfcd689ce175a9dfce0ec51f22e4fff367

Observation 6e7a7b2c-301e-406e-9e2a-af0ab2340228 · outbound

This paper cites Jointly aligning and predicting continuous emotion annotations,.

Probabilistic Permutation Invariant Training for Speech Separation Jointly aligning and predicting continuous emotion annotations,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-14T15:20:29.506911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:20:29.506911Z digest=sha256:9f96903863662fed2de4db51e26b69ff36443d233f56634506e0354cd6e1da25

Observation 19021b35-a0de-40b8-b5d7-bc27d66a6860 · outbound

This paper cites Progressive Neural Networks for Transfer Learning in Emotion Recognition.

Probabilistic Permutation Invariant Training for Speech Separation Progressive Neural Networks for Transfer Learning in Emotion Recognition

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-14T15:20:29.756396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.513891Z digest=sha256:75d1bae7f828061ff4a9f6321bfd5d5667490acd660fa37dca70e1fe270e0fe9

Observation f2877708-3683-4590-8046-8800b9a86458 · outbound

This paper cites A robust text depen- dent speaker identification using neural responses from the model of the auditory system,.

Probabilistic Permutation Invariant Training for Speech Separation A robust text depen- dent speaker identification using neural responses from the model of the auditory system,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.281874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.520220Z digest=sha256:aa95ee8f5d9ac66d598871500810ef21a2b91b8f50ad8bb43a6a37fb09258e2f

Observation 74ee84ae-9ed6-4953-81bb-3e9151f7a30e · outbound

This paper cites Speaker recognition by machines and humans: A tutorial review,.

Probabilistic Permutation Invariant Training for Speech Separation Speaker recognition by machines and humans: A tutorial review,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.263194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.533652Z digest=sha256:aa0171e7945ffa3b33485523a60b2104300ff4e5cc91ba8fa3485be72d3894cf

Observation 0d0bdba4-0089-4c4b-b0c9-c04072e2d893 · outbound

This paper cites Computational auditory scene analysis: Principles, algorithms, application.

Probabilistic Permutation Invariant Training for Speech Separation Computational auditory scene analysis: Principles, algorithms, application

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.244611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.541101Z digest=sha256:8b8b8867194eaa42a8e768cf81ae82a6fb2811a74c84a965243bcbc8d95f7193

Observation af1cfc9e-d248-4d63-b29b-5716bfad3978 · outbound

This paper cites Independent component analysis, a new concept?.

Probabilistic Permutation Invariant Training for Speech Separation Independent component analysis, a new concept?

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-14T15:20:29.546769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:20:29.546769Z digest=sha256:ce49e642ef16b38770ed4227227203fe6f46e6ef66fb4dd99c238b18f6e14bb5

Observation eebc0cae-dd79-4fee-b598-95c5791cfa32 · outbound

This paper cites One microphone source separation,.

Probabilistic Permutation Invariant Training for Speech Separation One microphone source separation,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.213430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.552499Z digest=sha256:07602629a26511c325af26b5722e02f003e1b3d45e6539ff898b27cd570fb375

Observation 933baa65-489e-4326-b000-fdfc3b4a38fa · outbound

This paper cites Convolutive speech bases and their applica- tion to supervised speech separation,.

Probabilistic Permutation Invariant Training for Speech Separation Convolutive speech bases and their applica- tion to supervised speech separation,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.189169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.558503Z digest=sha256:bbc41bf9282f091da036a3d2dad94c351b5ab5155e08945a56ddace1514b13ce

Observation 441c7873-8c9b-4c35-9611-91deb6fdc8e0 · outbound

This paper cites Supervised speech enhancement using online group-sparse convolutive nmf,.

Probabilistic Permutation Invariant Training for Speech Separation Supervised speech enhancement using online group-sparse convolutive nmf,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.165708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.565685Z digest=sha256:923a5fef9721643dd876b5913735227afaadefa98f87c29b4c258309770d6542

Observation 1aa477a2-daa1-4f07-b5e2-79ce8bf474fb · outbound

This paper cites On training targets for supervised speech separation,.

Probabilistic Permutation Invariant Training for Speech Separation On training targets for supervised speech separation,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.146640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.571112Z digest=sha256:f4812f1ca9a34e90b7ea589eaa0624abc4ccd18498c7529bc16cf74ce865238f

Observation bf028d8e-6626-45da-9d47-ae159921016e · outbound

This paper cites Joint optimization of masks and deep recurrent neural networks for monaural source separation,.

Probabilistic Permutation Invariant Training for Speech Separation Joint optimization of masks and deep recurrent neural networks for monaural source separation,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.123839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.578671Z digest=sha256:2bc2976b7874828fffd09044796360cee1b6e0a9e17daf99fd1f5c9b50296ed2

Observation d2cf1475-dbaa-4ae4-a208-7c3d0c87cc12 · outbound

This paper cites A deep ensemble learning method for monaural speech separation,.

Probabilistic Permutation Invariant Training for Speech Separation A deep ensemble learning method for monaural speech separation,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.106595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.587397Z digest=sha256:181d9dab060f8eed51d4ebcc125a90dcd732ecb9044f003e713bc1d74d5bc97e

Observation 9541543a-73e5-423f-ac2a-fbb8b2d1f478 · outbound

This paper cites Convolutional neu- ral network-based speech enhancement for cochlear implant re- cipients,.

Probabilistic Permutation Invariant Training for Speech Separation Convolutional neu- ral network-based speech enhancement for cochlear implant re- cipients,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.084573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.595388Z digest=sha256:516c12122c7ee7c73917e2abe09fce3c27fcd11f18c21f29f876ae54433fa16f

Observation 8b171cdd-f62c-4b64-8d1b-ac566114e68c · outbound

This paper cites Deep clus- tering: Discriminative embeddings for segmentation and separa- tion,.

Probabilistic Permutation Invariant Training for Speech Separation Deep clus- tering: Discriminative embeddings for segmentation and separa- tion,

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-14T15:20:29.602002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:20:29.602002Z digest=sha256:81fab7aae84cde0528aaee0ad1665eb8d5302f89d177355d19dcb85ba413cd55

Observation 808c30d0-e9ca-410b-ae9f-cd43e66686ee · outbound

This paper cites Single-Channel Multi-Speaker Separation using Deep Clustering.

Probabilistic Permutation Invariant Training for Speech Separation Single-Channel Multi-Speaker Separation using Deep Clustering

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-14T15:20:29.608107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:20:29.608107Z digest=sha256:1ccd0edbe678e4578457ec17db178c3e35b435c088e92740e5a55e3bf7e826cb

Observation bca57cc0-3633-4c1f-94e8-5aaf44cd867d · outbound

This paper cites Deep attractor network for single-microphone speaker separation,.

Probabilistic Permutation Invariant Training for Speech Separation Deep attractor network for single-microphone speaker separation,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.045507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.613778Z digest=sha256:42f3b937a1a1e3007c0e2398bc427615a1abd8ca7de4d7aefc03a7133927678f

Observation 6ce08327-26fb-4c59-8a71-9bbf13f66393 · outbound

This paper cites Permutation invari- ant training of deep models for speaker-independent multi-talker speech separation,.

Probabilistic Permutation Invariant Training for Speech Separation Permutation invari- ant training of deep models for speaker-independent multi-talker speech separation,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:30.024618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.619674Z digest=sha256:cc414c3a0612d839b215abc5c9f1c2d4e450aae638148bb78921644d51bb606e

Observation 1175545c-4583-406a-858e-e6dd5238818f · outbound

This paper cites Multitalker speech separation with utterance- level permutation invariant training of deep recurrent neural net- works,.

Probabilistic Permutation Invariant Training for Speech Separation Multitalker speech separation with utterance- level permutation invariant training of deep recurrent neural net- works,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:29.997508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.624728Z digest=sha256:a9cfa0c7f70d4d782a6ae6f4623386bb9ca3337c44fe7e2d0d0107da066f38fe

Observation 5fb62346-2a55-4dfd-9e58-febb1b5aabab · outbound

This paper cites Complex ratio mask- ing for monaural speech separation,.

Probabilistic Permutation Invariant Training for Speech Separation Complex ratio mask- ing for monaural speech separation,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:29.978763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.631319Z digest=sha256:c4c6b35b82fd7c1e8d82404441eda52d77cac230d6c95c2f31715b38f3149041

Observation 3ed0ef82-5a03-4873-a8e2-4211cbdaccab · outbound

This paper cites Soft-dtw: a differentiable loss func- tion for time-series,.

Probabilistic Permutation Invariant Training for Speech Separation Soft-dtw: a differentiable loss func- tion for time-series,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:29.961058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.636644Z digest=sha256:024865a8a442a9744a846f3e7e4f4959bbff572ec71be027660498619009a50c

Observation ad1a4f0c-90fa-418e-91c7-bf97376914a9 · outbound

This paper cites An audio- visual corpus for speech perception and automatic speech recog- nition,.

Probabilistic Permutation Invariant Training for Speech Separation An audio- visual corpus for speech perception and automatic speech recog- nition,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-14T15:20:29.642658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:20:29.642658Z digest=sha256:dfee7fa0ca95e624a43290ae0b08b44d2137565b7060ad8df9ae166c5fb8cef6

Observation 58c49a48-a3da-47fa-b4b6-b6d54174932c · outbound

This paper cites Monaural speech separation and recognition challenge,.

Probabilistic Permutation Invariant Training for Speech Separation Monaural speech separation and recognition challenge,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-14T15:20:29.648458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:20:29.648458Z digest=sha256:9ff116a2df050c6ab20e16935d9eba784ab030e3c71a94401a297d41ad2d92ae

Observation 452b56ea-a1e8-4b3e-9a6e-f4d53c0944f0 · outbound

This paper cites Teager–kaiser energy operators for overlapped speech detection,.

Probabilistic Permutation Invariant Training for Speech Separation Teager–kaiser energy operators for overlapped speech detection,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:29.921007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.653179Z digest=sha256:ed44537e14225bfa432a224ed97c01fad032c9ce0c9e9e8ca0fbc6a9476319e5

Observation 6cde6463-3bc1-4cf2-8fca-4d16d62806ac · outbound

This paper cites Assessing speaker en- gagement in 2-person debates: Overlap detection in united states presidential debates,.

Probabilistic Permutation Invariant Training for Speech Separation Assessing speaker en- gagement in 2-person debates: Overlap detection in united states presidential debates,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:29.903884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.658513Z digest=sha256:8625808b0aca2d3ebb78861037d189820efac60cd57d783a56dd139e1154ebbc

Observation f1c8d2f2-abac-478e-8816-706a33d1df6f · outbound

This paper cites Speech separation based on signal-noise-dependent deep neural networks for robust speech recognition,.

Probabilistic Permutation Invariant Training for Speech Separation Speech separation based on signal-noise-dependent deep neural networks for robust speech recognition,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:29.887618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.663835Z digest=sha256:4e3e4da3a10246195004342011d945cfe5189f8f6058f357f998e09427084832

Observation c14124d4-5c99-4867-b5e9-f43bd587bf3e · outbound

This paper cites Performance measure- ment in blind audio source separation,.

Probabilistic Permutation Invariant Training for Speech Separation Performance measure- ment in blind audio source separation,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:29.868783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.668737Z digest=sha256:9de315459f8e4dfcca5b9bc7f930647459581a6c8be6aed2984f6ebd2ebcafea

Observation cfd946b8-0cce-43ed-be5c-df5d43944aab · outbound

This paper cites Modeling perceptual similarity of audio signals for blind source separation evaluation,.

Probabilistic Permutation Invariant Training for Speech Separation Modeling perceptual similarity of audio signals for blind source separation evaluation,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:29.849740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.675130Z digest=sha256:9a039d40af80f119ff1bbe2bf665576cd3d23eedf5050369ccd2a70719bb8821

Observation 2c6a43c9-c5b8-4d7f-8911-128b35ff9090 · outbound

This paper cites Long short-term memory for speaker gen- eralization in supervised speech separation,.

Probabilistic Permutation Invariant Training for Speech Separation Long short-term memory for speaker gen- eralization in supervised speech separation,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T15:20:29.831508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.682290Z digest=sha256:5b010b5d7ebbe4b9cc167ad9342df6e1245f6f97594ea9bc8afd8a739e519369

Pith citing papers

Observation d1c30595-5684-40ec-a014-01b2e4bf24a7 · inbound

Probabilistic Permutation Invariant Training for Speech Separation cites this paper.

Probabilistic Permutation Invariant Training for Speech Separation Probabilistic Permutation Invariant Training for Speech Separation

Reference 1

Resolution
metadata mismatch
local_arxiv, observed 2026-08-14T15:20:29.813178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T15:20:29.404068Z digest=sha256:573eef69bfcb9fc497d2ec1f1864d0bf425927347667dfa31f65035f97952600