Paper Citation Record · LEDGER

Identifying and Calibrating Overconfidence in Noisy Speech Recognition

As of 20 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 2 inbound Pith citation observations for arXiv:2509.07195.

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

pith.paper-citation-record.v1
2509.07195 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T22:44:25.131506Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T08:54:56.253187Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T08:55:34.712184Z

Reference resolution

39 of 39 outbound references displayed

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External citation measurements

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Outbound references

Observation d2f0c863-d086-4d31-9902-82cba5c1a2e9 · outbound

This paper cites Confidence measures for speech recognition: A survey,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Confidence measures for speech recognition: A survey,

Reference 1

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This paper cites Evaluating OpenAI’s Whisper ASR: Perfor- mance analysis across diverse accents and speaker traits,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Evaluating OpenAI’s Whisper ASR: Perfor- mance analysis across diverse accents and speaker traits,

Reference 2

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Observation 53d015ce-d974-4eb9-8df9-ab2a0aa0effd · outbound

This paper cites Speech recognition in adverse conditions by humans and machines,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Speech recognition in adverse conditions by humans and machines,

Reference 3

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This paper cites Release from same-talker speech-in-speech masking: Effects of masker intelligibility and other contributing factors,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Release from same-talker speech-in-speech masking: Effects of masker intelligibility and other contributing factors,

Reference 4

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

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Robust speech recognition via large-scale weak supervi- sion,

Reference 5

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Observation c9518324-b963-4048-9122-73c1a4bf2967 · outbound

This paper cites Evaluation of a noise-robust dsr front-end on aurora databases.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Evaluation of a noise-robust dsr front-end on aurora databases

Reference 6

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Observation c6effed1-3918-4cd2-94ea-af48da200399 · outbound

This paper cites A minimum- mean-square-error noise reduction algorithm on mel-frequency cepstra for robust speech recognition,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition A minimum- mean-square-error noise reduction algorithm on mel-frequency cepstra for robust speech recognition,

Reference 7

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This paper cites An investigation of deep neural net- works for noise robust speech recognition,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition An investigation of deep neural net- works for noise robust speech recognition,

Reference 8

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Observation 1adff0b3-6cd3-4b6d-bc71-5fe962850c02 · outbound

This paper cites Audio augmentation for speech recognition.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Audio augmentation for speech recognition

Reference 9

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Observation f1ccc55c-c23a-4dec-be40-8b249925fa0e · outbound

This paper cites SpecAugment: A simple data augmentation method for automatic speech recognition,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition SpecAugment: A simple data augmentation method for automatic speech recognition,

Reference 10

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Observation ac0044df-8376-4b0d-b02f-157fd735d014 · outbound

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

Identifying and Calibrating Overconfidence in Noisy Speech Recognition wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 11

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This paper cites Speech en- hancement and recognition using multi-task learning of long short-term memory recurrent neural networks.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Speech en- hancement and recognition using multi-task learning of long short-term memory recurrent neural networks

Reference 12

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This paper cites Improved estimation, evaluation and applications of confidence measures for speech recognition.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Improved estimation, evaluation and applications of confidence measures for speech recognition

Reference 13

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Observation c6198890-712c-4b51-8f97-240c4ad5af71 · outbound

This paper cites Posterior probability decoding, confi- dence estimation and system combination,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Posterior probability decoding, confi- dence estimation and system combination,

Reference 14

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This paper cites Confidence measures for large vocabulary continuous speech recognition,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Confidence measures for large vocabulary continuous speech recognition,

Reference 15

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This paper cites High-level approaches to confidence estimation in speech recognition,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition High-level approaches to confidence estimation in speech recognition,

Reference 16

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Observation 02522c72-bc47-4906-882d-b8c7584e22a5 · outbound

This paper cites Combining information sources for confidence estimation with crf models.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Combining information sources for confidence estimation with crf models

Reference 17

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Observation f09b2e3b-e391-4efe-bd69-39167260e1a5 · outbound

This paper cites Calibration of confidence measures in speech recognition,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Calibration of confidence measures in speech recognition,

Reference 18

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This paper cites On calibration of modern neural networks,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition On calibration of modern neural networks,

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This paper cites Improving ASR confidence scores for Alexa using acoustic and hy- pothesis embeddings,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Improving ASR confidence scores for Alexa using acoustic and hy- pothesis embeddings,

Reference 20

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This paper cites Confidence measures in encoder-decoder models for speech recognition.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Confidence measures in encoder-decoder models for speech recognition

Reference 21

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This paper cites Confidence estimation for attention-based sequence-to- sequence models for speech recognition,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Confidence estimation for attention-based sequence-to- sequence models for speech recognition,

Reference 22

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Observation b1d96f42-251a-4168-ab6b-9aba5303b142 · outbound

This paper cites Learning word-level confidence for subword end- to-end asr,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Learning word-level confidence for subword end- to-end asr,

Reference 23

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This paper cites Blstm-based confi- dence estimation for end-to-end speech recognition,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Blstm-based confi- dence estimation for end-to-end speech recognition,

Reference 24

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This paper cites Multi-task learning for end-to-end asr word and utterance confidence with deletion prediction,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Multi-task learning for end-to-end asr word and utterance confidence with deletion prediction,

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This paper cites Adopting Whisper for confidence estimation,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Adopting Whisper for confidence estimation,

Reference 26

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Identifying and Calibrating Overconfidence in Noisy Speech Recognition Improving confidence estimation on out-of-domain data for end-to-end speech recognition,

Reference 27

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Observation dba58c5b-5b66-487a-88b1-5f898488be96 · outbound

This paper cites Fast entropy-based methods of word-level confidence estimation for end-to-end automatic speech recognition,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Fast entropy-based methods of word-level confidence estimation for end-to-end automatic speech recognition,

Reference 28

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This paper cites Utterance-level neural confidence measure for end- to-end children speech recognition,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Utterance-level neural confidence measure for end- to-end children speech recognition,

Reference 29

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Identifying and Calibrating Overconfidence in Noisy Speech Recognition Proper error estimation and calibration for attention-based encoder-decoder models,

Reference 30

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This paper cites Calibration of pre-trained transformers,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Calibration of pre-trained transformers,

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This paper cites An evaluation of word- level confidence estimation for end-to-end automatic speech recogni- tion,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition An evaluation of word- level confidence estimation for end-to-end automatic speech recogni- tion,

Reference 32

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This paper cites Calibrated Selective Classification.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Calibrated Selective Classification

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Identifying and Calibrating Overconfidence in Noisy Speech Recognition Improving Predictor Reliability with Selective Recalibration

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This paper cites LibriTTS: A corpus derived from librispeech for text-to-speech,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition LibriTTS: A corpus derived from librispeech for text-to-speech,

Reference 35

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This paper cites The revised speech perception in noise test (R-SPIN) in a multiple signal-to-noise ratio paradigm,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition The revised speech perception in noise test (R-SPIN) in a multiple signal-to-noise ratio paradigm,

Reference 36

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Observation d1b4ce1b-bd7d-4fb9-a6ff-a11ba56d93df · outbound

This paper cites From WER and RIL to MER and WIL: improved evaluation measures for connected speech recognition.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition From WER and RIL to MER and WIL: improved evaluation measures for connected speech recognition

Reference 37

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This paper cites Soft calibration objectives for neural networks,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Soft calibration objectives for neural networks,

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This paper cites Access: Advancing innovation: Nsf’s advanced cyberinfrastructure co- ordination ecosystem: Services & support,.

Identifying and Calibrating Overconfidence in Noisy Speech Recognition Access: Advancing innovation: Nsf’s advanced cyberinfrastructure co- ordination ecosystem: Services & support,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:44:25.174929Z

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Pith citing papers

Observation 34620f83-72d2-42d9-ae56-d62c19d74753 · inbound

RAS: a Reliability Oriented Metric for Automatic Speech Recognition cites this paper.

RAS: a Reliability Oriented Metric for Automatic Speech Recognition Identifying and Calibrating Overconfidence in Noisy Speech Recognition

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Observation 56a771c9-1bae-49c8-bc6d-30d924b9f279 · inbound

RAS: a Reliability Oriented Metric for Automatic Speech Recognition cites this paper.

RAS: a Reliability Oriented Metric for Automatic Speech Recognition Identifying and Calibrating Overconfidence in Noisy Speech Recognition

Reference 19

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