Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis | Paper Citation Record

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This paper cites Challenges and opportunities in processing low resource languages: A study on persian,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Challenges and opportunities in processing low resource languages: A study on persian,

Reference 1

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This paper cites An investigation on ini- tialization schemes for multilayer perceptron training using multilingual data and their effect on asr performance,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis An investigation on ini- tialization schemes for multilayer perceptron training using multilingual data and their effect on asr performance,

Reference 2

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This paper cites Multilingual models with language embeddings for low- resource speech recognition,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Multilingual models with language embeddings for low- resource speech recognition,

Reference 3

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This paper cites Towards a common under- standing of contributing factors for cross-lingual transfer in multilingual language models: A review,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Towards a common under- standing of contributing factors for cross-lingual transfer in multilingual language models: A review,

Reference 4

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This paper cites Choosing transfer languages for cross- lingual learning,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Choosing transfer languages for cross- lingual learning,

Reference 5

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Observation ed5e83ef-8b83-41c1-a250-b56c4e5613d1 · outbound

This paper cites Sequence-based multi-lingual low resource speech recognition,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Sequence-based multi-lingual low resource speech recognition,

Reference 6

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This paper cites Exploiting adapters for cross-lingual low-resource speech recognition,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Exploiting adapters for cross-lingual low-resource speech recognition,

Reference 7

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This paper cites Improving cross-lingual transfer learning for end-to-end speech recognition with speech translation,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Improving cross-lingual transfer learning for end-to-end speech recognition with speech translation,

Reference 8

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This paper cites Cross-lingual subspace gaussian mixture models for low-resource speech recognition,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Cross-lingual subspace gaussian mixture models for low-resource speech recognition,

Reference 9

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This paper cites Cross-language end-to-end speech recognition research based on transfer learning for the low-resource tujia language,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Cross-language end-to-end speech recognition research based on transfer learning for the low-resource tujia language,

Reference 10

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This paper cites Linguistic disparities in cross-language automatic speech recognition transfer from arabic to tashlhiyt,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Linguistic disparities in cross-language automatic speech recognition transfer from arabic to tashlhiyt,

Reference 11

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This paper cites Cross-lingual portability of chinese and english neural network features for french and german lvcsr,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Cross-lingual portability of chinese and english neural network features for french and german lvcsr,

Reference 12

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This paper cites Development of multi- lingual asr using globalphone for less-resourced languages: The case of ethiopian languages.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Development of multi- lingual asr using globalphone for less-resourced languages: The case of ethiopian languages

Reference 13

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This paper cites Using large self-supervised models for low-resource speech recognition.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Using large self-supervised models for low-resource speech recognition

Reference 14

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This paper cites Cam: A cross-lingual adaptation framework for low-resource language speech recognition,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Cam: A cross-lingual adaptation framework for low-resource language speech recognition,

Reference 15

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This paper cites Cross-language knowledge transfer using multilingual deep neural network with shared hidden layers,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Cross-language knowledge transfer using multilingual deep neural network with shared hidden layers,

Reference 16

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This paper cites Multilingual speech recognition for turkic languages,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Multilingual speech recognition for turkic languages,

Reference 17

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This paper cites A comparison between morphological complexity measures: typological data vs. lan- guage corpora,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis A comparison between morphological complexity measures: typological data vs. lan- guage corpora,

Reference 18

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This paper cites Frequency of occurrence of phonemes in conversational english,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Frequency of occurrence of phonemes in conversational english,

Reference 19

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This paper cites Grambank reveals the importance of genealogical constraints on linguistic diversity and highlights the impact of language loss,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Grambank reveals the importance of genealogical constraints on linguistic diversity and highlights the impact of language loss,

Reference 20

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This paper cites Conformer: Convolution-augmented transformer for speech recognition,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Conformer: Convolution-augmented transformer for speech recognition,

Reference 21

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This paper cites Un- supervised cross-lingual representation learning for speech recognition,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Un- supervised cross-lingual representation learning for speech recognition,

Reference 22

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This paper cites Documenting and researching endangered languages: The pangloss collection,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Documenting and researching endangered languages: The pangloss collection,

Reference 23

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This paper cites Methods of language docu- mentation in the dobes program,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Methods of language docu- mentation in the dobes program,

Reference 24

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This paper cites Simple and effective zero-shot cross- lingual phoneme recognition,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Simple and effective zero-shot cross- lingual phoneme recognition,

Reference 25

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Observation e1db5414-d839-4cd8-b2fc-37a5176f473b · outbound

This paper cites Dif- ferentiable allophone graphs for language-universal speech recognition,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Dif- ferentiable allophone graphs for language-universal speech recognition,

Reference 26

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This paper cites Universal automatic phonetic transcription into the international phonetic alphabet,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Universal automatic phonetic transcription into the international phonetic alphabet,

Reference 27

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This paper cites Phono- logically aware neural model for named entity recognition in low resource transfer settings,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Phono- logically aware neural model for named entity recognition in low resource transfer settings,

Reference 28

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Observation 425577c8-118e-41da-b1e8-415f5d0d27b8 · outbound

This paper cites Kernel density estimation and its application,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Kernel density estimation and its application,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:49.561720Z

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This paper cites Improving the bandwidth selection in kernel equating,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Improving the bandwidth selection in kernel equating,

Reference 30

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This paper cites Haspelmath, M.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Haspelmath, M

Reference 31

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This paper cites Common voice: A massively-multilingual speech corpus,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Common voice: A massively-multilingual speech corpus,

Reference 32

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This paper cites Epitran: Precision g2p for many languages,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Epitran: Precision g2p for many languages,

Reference 33

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This paper cites Predicting positive transfer for improved low-resource speech recognition using acoustic pseudo-tokens.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Predicting positive transfer for improved low-resource speech recognition using acoustic pseudo-tokens

Reference 34

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This paper cites Attention is all you need,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Attention is all you need,

Reference 35

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This paper cites Espnet: Efficient spatial pyramid of dilated convolutions for semantic segmentation,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Espnet: Efficient spatial pyramid of dilated convolutions for semantic segmentation,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:49.365819Z

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This paper cites Phoneme level language models for sequence based low resource asr,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Phoneme level language models for sequence based low resource asr,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:49.354937Z

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This paper cites Roman jakobson’s conception of «sprachbund»,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Roman jakobson’s conception of «sprachbund»,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:49.305273Z

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This paper cites The history of turkic,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis The history of turkic,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:49.167744Z

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This paper cites On the kurdish language,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis On the kurdish language,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:49.155396Z

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This paper cites The Performance Evaluation of Attention-Based Neural ASR under Mixed Speech Input.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis The Performance Evaluation of Attention-Based Neural ASR under Mixed Speech Input

Reference 41

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Observation ac2ccf1d-87ed-4c19-8f71-8c9caceff47a · outbound

This paper cites Improving automatic speech recognition performance for low-resource languages with self-supervised models,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Improving automatic speech recognition performance for low-resource languages with self-supervised models,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:49.143142Z

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Observation c9cfbc7d-c7e3-4453-9944-c047f52c9c39 · outbound

This paper cites Multilingual self- supervised speech representations improve the speech recognition of low-resource african languages with codeswitching,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Multilingual self- supervised speech representations improve the speech recognition of low-resource african languages with codeswitching,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:49.039642Z

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Observation c0c69210-2371-4a2a-95c9-729ba58d672d · outbound

This paper cites Meta-adaptable- adapter: Efficient adaptation of self-supervised models for low-resource speech recognition,.

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis Meta-adaptable- adapter: Efficient adaptation of self-supervised models for low-resource speech recognition,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:48.950041Z

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Observation 1aca26f0-8eab-4fb4-bc72-07e26d0daac6 · outbound

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

Improving Cross-Lingual Phonetic Representation of Low-Resource Languages Through Language Similarity Analysis wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 45

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