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Paper Citation Record · LEDGER

Complexity boosted adaptive training for better low resource ASR performance

As of 16 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2412.00877.

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

pith.paper-citation-record.v1
2412.00877 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:59:13.276922Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:59:13.181738Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T04:59:13.376269Z

Reference resolution

31 of 31 outbound references displayed

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  • verified fuzzy21
  • unresolved6
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External citation measurements

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Outbound references

Observation 636cd41e-0758-465e-b063-8dd6dceaa173 · outbound

This paper cites Besides the model architecture, the performance of ASR systems relies heavily on the availability of large and di- verse training data with transcripts.

Complexity boosted adaptive training for better low resource ASR performance Besides the model architecture, the performance of ASR systems relies heavily on the availability of large and di- verse training data with transcripts

Reference 1

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Observation ff154d97-0682-4123-a436-4b9f8037f992 · outbound

This paper cites It introduces feature domain time masking and fre- quency masking to data augmentation.

Complexity boosted adaptive training for better low resource ASR performance It introduces feature domain time masking and fre- quency masking to data augmentation

Reference 2

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Observation e5648e41-b9be-4db0-9877-3d03f89ffc10 · outbound

This paper cites The operation of the mask remains at twice in WeNet Conformer.

Complexity boosted adaptive training for better low resource ASR performance The operation of the mask remains at twice in WeNet Conformer

Reference 3

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Observation 093d14bd-31f7-483d-98da-09366a4fec3c · outbound

This paper cites Dataset We perform our experiments on two datasets: AISHELL-1 [23] and LibriSpeech [24].

Complexity boosted adaptive training for better low resource ASR performance Dataset We perform our experiments on two datasets: AISHELL-1 [23] and LibriSpeech [24]

Reference 4

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Observation 3b2247d6-730b-4131-84d3-eccbd235d80f · outbound

This paper cites Ini- tially, we apply regularization to the training process by utilizing the intermediate CTC loss regularization.

Complexity boosted adaptive training for better low resource ASR performance Ini- tially, we apply regularization to the training process by utilizing the intermediate CTC loss regularization

Reference 5

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Observation ee2c21b1-a6b2-4eb6-808f-18c1195263a6 · outbound

This paper cites Sapaugment: Learning a sample adaptive policy for data augmentation,.

Complexity boosted adaptive training for better low resource ASR performance Sapaugment: Learning a sample adaptive policy for data augmentation,

Reference 6

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Observation f47c79d8-4c03-43eb-ba5d-94721ba4c816 · outbound

This paper cites SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition.

Complexity boosted adaptive training for better low resource ASR performance SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

Reference 7

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Observation deea2ba0-ebb0-4466-8018-9eb2b703880f · outbound

This paper cites Listen, attend and spell: A neural network for large vocab- ulary conversational speech recognition,.

Complexity boosted adaptive training for better low resource ASR performance Listen, attend and spell: A neural network for large vocab- ulary conversational speech recognition,

Reference 8

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Observation 85c88d28-a3cd-4a5c-8a02-3258efccf081 · outbound

This paper cites Attention-based mod- els for speech recognition,.

Complexity boosted adaptive training for better low resource ASR performance Attention-based mod- els for speech recognition,

Reference 9

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Observation dd44d7b4-33e5-4d48-9003-f1f078178743 · outbound

This paper cites Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data Augmentation.

Complexity boosted adaptive training for better low resource ASR performance Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data Augmentation

Reference 10

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Observation 51b0be4c-6c6f-4a8e-803f-ae6cffdd3263 · outbound

This paper cites ASR data augmentation in low-resource settings using cross-lingual multi-speaker TTS and cross-lingual voice conversion.

Complexity boosted adaptive training for better low resource ASR performance ASR data augmentation in low-resource settings using cross-lingual multi-speaker TTS and cross-lingual voice conversion

Reference 11

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Observation cf33eb89-4f5b-4f1b-a293-1026a3dba7a3 · outbound

This paper cites On-the-Fly Aligned Data Augmentation for Sequence-to-Sequence ASR.

Complexity boosted adaptive training for better low resource ASR performance On-the-Fly Aligned Data Augmentation for Sequence-to-Sequence ASR

Reference 12

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Observation bed62a36-acf5-49ae-a377-c4d014c4e75f · outbound

This paper cites An inves- tigation of deep neural networks for noise robust speech recog- nition,.

Complexity boosted adaptive training for better low resource ASR performance An inves- tigation of deep neural networks for noise robust speech recog- nition,

Reference 13

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Observation 04b197bb-a089-47c2-ba0c-e2751d6cd2aa · outbound

This paper cites A study on data augmen- tation of reverberant speech for robust speech recognition,.

Complexity boosted adaptive training for better low resource ASR performance A study on data augmen- tation of reverberant speech for robust speech recognition,

Reference 14

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Observation 7f157ab6-17b3-4134-97db-263c957a0284 · outbound

This paper cites Squeezeformer: An efficient transformer for automatic speech recognition,.

Complexity boosted adaptive training for better low resource ASR performance Squeezeformer: An efficient transformer for automatic speech recognition,

Reference 15

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Observation fe585277-334c-40c9-b29e-0d98ae24ea23 · outbound

This paper cites Various aux- iliary loss functions have been explored for different architectures.

Complexity boosted adaptive training for better low resource ASR performance Various aux- iliary loss functions have been explored for different architectures

Reference 16

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Observation 00bf2ea5-3ed5-40d5-a758-a4ec8bdc38e4 · outbound

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

Complexity boosted adaptive training for better low resource ASR performance E-branchformer: Branchformer with enhanced merging for speech recognition,

Reference 17

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Observation f4936376-87d1-403d-b090-55eeea420f31 · outbound

This paper cites Complexity boosted adaptive training for better low resource ASR performance.

Complexity boosted adaptive training for better low resource ASR performance Complexity boosted adaptive training for better low resource ASR performance

Reference 18

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Observation 3e7047f1-e9b6-4e9d-a336-7b7d334137f4 · outbound

This paper cites Improving Mandarin Speech Recogntion with Block-augmented Transformer.

Complexity boosted adaptive training for better low resource ASR performance Improving Mandarin Speech Recogntion with Block-augmented Transformer

Reference 19

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Observation f1057e79-b45f-4d7e-8f0b-434465ea3e33 · outbound

This paper cites Efficient conformer: Progressive downsampling and grouped attention for automatic speech recognition,.

Complexity boosted adaptive training for better low resource ASR performance Efficient conformer: Progressive downsampling and grouped attention for automatic speech recognition,

Reference 20

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Observation 2d6cc468-aa8c-4f87-b49e-1ff1db78041d · outbound

This paper cites Audio augmentation for speech recognition,.

Complexity boosted adaptive training for better low resource ASR performance Audio augmentation for speech recognition,

Reference 21

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Observation 30c59f6a-5d1b-4aa1-b93b-ff1e8a629b24 · outbound

This paper cites Connectionist temporal classification: la- belling unsegmented sequence data with recurrent neural net- works,.

Complexity boosted adaptive training for better low resource ASR performance Connectionist temporal classification: la- belling unsegmented sequence data with recurrent neural net- works,

Reference 22

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Observation a714ec34-6ccb-4674-99ad-b714cc59d40f · outbound

This paper cites Sequence Transduction with Recurrent Neural Networks.

Complexity boosted adaptive training for better low resource ASR performance Sequence Transduction with Recurrent Neural Networks

Reference 23

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Observation 7104b695-2ac3-457c-95a8-c5e2f2cdd21c · outbound

This paper cites Attention is all you need,.

Complexity boosted adaptive training for better low resource ASR performance Attention is all you need,

Reference 24

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Observation e5eca047-f1a5-416d-b76f-83b3f53434b3 · outbound

This paper cites Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition.

Complexity boosted adaptive training for better low resource ASR performance Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition

Reference 25

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 87443b2b-e9ba-47bd-8782-f2515900cb7c · outbound

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

Complexity boosted adaptive training for better low resource ASR performance Intermediate loss regular- ization for ctc-based speech recognition,

Reference 26

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Observation f7d8372a-6714-47ac-b3f5-77c74528a2ee · outbound

This paper cites Conformer: Convolution-augmented Transformer for Speech Recognition.

Complexity boosted adaptive training for better low resource ASR performance Conformer: Convolution-augmented Transformer for Speech Recognition

Reference 27

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Observation 6260f095-42ec-4c31-9990-41765f8c7ea3 · outbound

This paper cites WeNet: Production oriented Streaming and Non-streaming End-to-End Speech Recognition Toolkit.

Complexity boosted adaptive training for better low resource ASR performance WeNet: Production oriented Streaming and Non-streaming End-to-End Speech Recognition Toolkit

Reference 28

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Observation e07e22b5-3586-42d3-849b-3bfa036020b0 · outbound

This paper cites Paris, Incomplete beta functions , NIST Handbook of Mathematical Functions, Cambridge University Press, 2010.

Complexity boosted adaptive training for better low resource ASR performance Paris, Incomplete beta functions , NIST Handbook of Mathematical Functions, Cambridge University Press, 2010

Reference 29

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Observation b3d33752-2c54-4efd-909c-cd7dbf79e207 · outbound

This paper cites Aishell-1: An open-source mandarin speech corpus and a speech recognition baseline,.

Complexity boosted adaptive training for better low resource ASR performance Aishell-1: An open-source mandarin speech corpus and a speech recognition baseline,

Reference 30

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation dd3faef0-191a-4a5e-99d3-7080c5f13a29 · outbound

This paper cites Librispeech: an asr corpus based on public do- main audio books,.

Complexity boosted adaptive training for better low resource ASR performance Librispeech: an asr corpus based on public do- main audio books,

Reference 31

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Pith citing papers

Observation f4936376-87d1-403d-b090-55eeea420f31 · inbound

Complexity boosted adaptive training for better low resource ASR performance cites this paper.

Complexity boosted adaptive training for better low resource ASR performance Complexity boosted adaptive training for better low resource ASR performance

Reference 18

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local_arxiv, observed 2026-08-12T04:59:13.379242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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