---
title: "Who cites Daniel Povey — 195 papers of our library"
description: "195 papers of the Elamur Research library cite the works of Daniel Povey, found in their bibliographies; the most cited first."
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---
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# Who cites Daniel Povey

197 citations of their works from 195 papers of our library (of the 149,439 whose bibliographies we read) · 58 with a page here, the most cited first · [← Daniel Povey](https://md.research.elamur.ai/free/en/authors/daniel-povey/)

1. **[SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition](https://md.research.elamur.ai/free/en/papers/park-2019-specaugment-simple-data-augmentation-method/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Daniel S. Park, William Chan, Yu Zhang, et al.*2019 · 3,837 citations*
2. [**Robust Speech Recognition via Large-Scale Weak Supervision arXiv:2212.04356**Alec Radford, Jong Wook Kim, Tao Xu, et al.*2022 · 2,546 citations*](https://md.research.elamur.ai/free/en/papers/radford-2022-robust-speech-recognition-large-scale/)
3. [**Deep Speech 2: End-to-End Speech Recognition in English and Mandarin arXiv:1512.02595**Dario Amodei, Rishita Anubhai, Eric Battenberg, et al.*2015 · 2,341 citations*](https://md.research.elamur.ai/free/en/papers/amodei-2015-deep-speech-2-end-end/)
4. [**Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) arXiv:1511.07289**Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter*2015 · 2,314 citations*](https://md.research.elamur.ai/free/en/papers/clevert-2015-fast-accurate-deep-network-learning/)
5. [**Deep Speech: Scaling up end-to-end speech recognition arXiv:1412.5567**Awni Hannun, Carl Case, Jared Casper, et al.*2014 · 1,600 citations*](https://md.research.elamur.ai/free/en/papers/hannun-2014-deep-speech-scaling-up-end/)
6. **[SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities](https://md.research.elamur.ai/free/en/papers/zhang-2023-speechgpt-empowering-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dong Zhang, Shimin Li, Xin Zhang, et al.*2023 · 347 citations*
7. **[Long Short-Term Memory Neural Networks for Chinese Word Segmentation](https://md.research.elamur.ai/free/en/papers/chen-2015-long-short-term-memory-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xinchi Chen, Xipeng Qiu, Chenxi Zhu, et al.*2015 · 336 citations*
8. [**Long-term Recurrent Convolutional Networks for Visual Recognition and Description arXiv:1411.4389**Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach, et al.*2014 · 245 citations*](https://md.research.elamur.ai/free/en/papers/donahue-2014-long-term-recurrent-convolutional-networks/)
9. **[Arabic natural language processing: An overview](https://md.research.elamur.ai/free/en/papers/guellil-2019-arabic-natural-language-processing-overview/) [Journal of King Saud University - Computer and Information Sciences](https://md.research.elamur.ai/free/en/venues/journal-of-king-saud-university-computer-and-information-sciences/)**Imane Guellil, Houda Saadane, Faical Azouaou, et al.*2019 · 239 citations*
10. [**SALMONN: Towards Generic Hearing Abilities for Large Language Models arXiv:2310.13289**Changli Tang, Wenyi Yu, Guangzhi Sun, et al.*2023 · 209 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-salmonn-towards-generic-hearing-abilities/)
11. **[The IBM 2015 English Conversational Telephone Speech Recognition System](https://md.research.elamur.ai/free/en/papers/saon-2015-ibm-2015-english-conversational-telephone/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**George Saon, Hong-Kwang J. Kuo, Steven Rennie, et al.*2015 · 97 citations*
12. **[AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling](https://md.research.elamur.ai/free/en/papers/zhan-2024-anygpt-unified-multimodal-llm-discrete/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jun Zhan, Junqi Dai, Jiasheng Ye, et al.*2024 · 95 citations*
13. **[AudioBench: A Universal Benchmark for Audio Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-audiobench-universal-benchmark-audio-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Xunlong Zou, Geyu Lin, et al.*2025 · 77 citations*
14. **[Recent Advances in Speech Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/cui-2025-recent-advances-speech-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqian Cui, Dianzhi Yu, Xiaoqi Jiao, et al.*2025 · 69 citations*
15. [**GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken Chatbot arXiv:2412.02612**Aohan Zeng, Zhengxiao Du, Mingdao Liu, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-glm-4-voice-intelligent/)
16. **[Transformer-Based Multi-Aspect Multi-Granularity Non-Native English Speaker Pronunciation Assessment](https://md.research.elamur.ai/free/en/papers/gong-2022-transformer-based-multi-aspect-multi/) [IEEE International Conference on Acoustics Speech and Signal Processing](https://md.research.elamur.ai/free/en/venues/ieee-international-conference-on-acoustics-speech-and-signal-processing/)**Yuan Gong, Ziyi Chen, Iek-Heng Chu, et al.*2022 · 59 citations*
17. [**Kimi-Audio Technical Report arXiv:2504.18425**KimiTeam, Ding Ding, Zeqian Ju, et al.*2025 · 57 citations*](https://md.research.elamur.ai/free/en/papers/kimiteam-2025-kimi-audio-technical-report/)
18. **[What Do Self-Supervised Speech Models Know About Words?](https://md.research.elamur.ai/free/en/papers/pasad-2024-what-do-self-supervised-speech/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ankita Pasad, Chung-Ming Chien, Shane Settle, et al.*2024 · 51 citations*
19. **[AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR](https://md.research.elamur.ai/free/en/papers/olatunji-2023-afrispeech-200-pan-african-accented/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tobi Olatunji, Tejumade Afonja, Aditya Yadavalli, et al.*2023 · 45 citations*
20. **[ArzEn-ST: A Three-way Speech Translation Corpus for Code-Switched Egyptian Arabic-English](https://md.research.elamur.ai/free/en/papers/hamed-2022-arzen-st-three-way-speech/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Injy Hamed, Nizar Habash, Slim Abdennadher, et al.*2022 · 26 citations*
21. **[Distilling an End-to-End Voice Assistant Without Instruction Training Data](https://md.research.elamur.ai/free/en/papers/held-2025-distilling-end-end-voice-assistant/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**William Held, Yanzhe Zhang, Minzhi Li, et al.*2025 · 18 citations*
22. **[Morphology-aware Word-Segmentation in Dialectal Arabic Adaptation of Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/tawfik-2019-morphology-aware-word-segmentation-dialectal/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Ahmed Tawfik, Mahitab Emam, Khaled Essam, et al.*2019 · 18 citations*
23. [**Scaling Speech-Text Pre-training with Synthetic Interleaved Data arXiv:2411.17607**Aohan Zeng, Zhengxiao Du, Mingdao Liu, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-scaling-speech-text-pre-training/)
24. **[Paralinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation](https://md.research.elamur.ai/free/en/papers/kim-2024-paralinguistics-aware-speech-empowered-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Heeseung Kim, Soonshin Seo, Kyeongseok Jeong, et al.*2024 · 13 citations*
25. **[QualiSpeech: A Speech Quality Assessment Dataset with Natural Language Reasoning and Descriptions](https://md.research.elamur.ai/free/en/papers/wang-2025-qualispeech-speech-quality-assessment-dataset/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siyin Wang, Wenyi Yu, Xianzhao Chen, et al.*2025 · 12 citations*
26. [**Fanar 2.0: Arabic Generative AI Stack arXiv:2603.16397**FANAR TEAM, Ummar Abbas, Mohammad Shahmeer Ahmad, et al.*2026 · 11 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-fanar-2-0-arabic-generative/)
27. [**ArzEn-MultiGenre: An aligned parallel dataset of Egyptian Arabic song lyrics, novels, and subtitles, with English translations arXiv:2508.01411 · Data in Brief, 54**Rania Al-Sabbagh*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/al-sabbagh-2025-arzen-multigenre-aligned-parallel-dataset/)
28. **[Leveraging Allophony in Self-Supervised Speech Models for Atypical Pronunciation Assessment](https://md.research.elamur.ai/free/en/papers/choi-2025-leveraging-allophony-self-supervised-speech/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kwanghee Choi, Eunjung Yeo, Kalvin Chang, et al.*2025 · 8 citations*
29. **[Loquacious Set: 25,000 Hours of Transcribed and Diverse English Speech Recognition Data for Research and Commercial Use](https://md.research.elamur.ai/free/en/papers/parcollet-2025-loquacious-set-25-000-hours/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Titouan Parcollet, Yuan Tseng, Shucong Zhang, et al.*2025 · 7 citations*
30. **[ZIPA: A family of efficient models for multilingual phone recognition](https://md.research.elamur.ai/free/en/papers/zhu-2025-zipa-family-efficient-models-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jian Zhu, Farhan Samir, Eleanor Chodroff, et al.*2025 · 7 citations*
31. [**DARTS: Dialectal Arabic Transcription System arXiv:1909.12163**Sameer Khurana, Ahmed Ali, James Glass*2019 · 7 citations*](https://md.research.elamur.ai/free/en/papers/khurana-2019-darts-dialectal-arabic-transcription-system/)
32. [**MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction arXiv:2604.27393**Junbo Cui, Bokai Xu, Chongyi Wang, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/cui-2026-minicpm-o-4-5/)
33. [**Speak & Improve Corpus 2025: an L2 English Speech Corpus for Language Assessment and Feedback arXiv:2412.11986**Kate Knill, Diane Nicholls, Mark J.F. Gales, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/knill-2024-speak-improve-corpus-2025-l2/)
34. **[The WAW Corpus: The First Corpus of Interpreted Speeches and their Translations for English and Arabic](https://md.research.elamur.ai/free/en/papers/abdelali-2018-waw-corpus-first-corpus-interpreted/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ahmed Abdelali, Irina Temnikova, Samy Hedaya, et al.*2018 · 5 citations*
35. [**Speak & Improve Challenge 2025: Tasks and Baseline Systems arXiv:2412.11985**Mengjie Qian, Kate Knill, Stefano Banno, et al.*2024 · 3 citations*](https://md.research.elamur.ai/free/en/papers/qian-2024-speak-improve-challenge-2025-tasks/)
36. **[Efficient Training for Cross-lingual Speech Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-efficient-training-cross-lingual-speech/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yan Zhou, Qingkai Fang, Yun Hong, et al.*2026 · 2 citations*
37. **[J-CHAT: Japanese Large-scale Spoken Dialogue Corpus for Spoken Dialogue Language Modeling](https://md.research.elamur.ai/free/en/papers/nakata-2026-j-chat-japanese-large-scale/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Wataru Nakata, Kentaro Seki, Hitomi Yanaka, et al.*2026 · 2 citations*
38. **[LLM-ForcedAligner: A Non-Autoregressive and Accurate LLM-Based Forced Aligner for Multilingual and Long-Form Speech](https://md.research.elamur.ai/free/en/papers/mu-2026-llm-forcedaligner-non-autoregressive-accurate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bingshen Mu, Xian Shi, Xiong Wang, et al.*2026 · 2 citations*
39. [**Attention-based sequence-to-sequence model for speech recognition: development of state-of-the-art system on LibriSpeech and its application to non-native English arXiv:1810.13088**Yan Yin, Ramon Prieto, Bin Wang, et al.*2018 · 2 citations*](https://md.research.elamur.ai/free/en/papers/yin-2018-attention-based-sequence-sequence-model/)
40. **[HARNESS: Lightweight Distilled Arabic Speech Foundation Models](https://md.research.elamur.ai/free/en/papers/sukhadia-2026-harness-lightweight-distilled-arabic-speech/) [Speech Language Models in Low-Resource Settings: Performance, Evaluation, and Bias Analysis (SPEAKABLE) @ LREC](https://md.research.elamur.ai/free/en/venues/speakable/)**Vrunda Nileshkumar Sukhadia, Shammur Absar Chowdhury*2026 · 1 citation*
41. **[Rubric-Guided Fine-tuning of SpeechLLMs for Multi-Aspect, Multi-Rater L2 Reading-Speech Assessment](https://md.research.elamur.ai/free/en/papers/parikh-2026-rubric-guided-fine-tuning-speechllms/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aditya Kamlesh Parikh, Cristian Tejedor-García, Catia Cucchiarini, et al.*2026 · 1 citation*
42. **[UltraEval-Audio: A Unified Framework for Comprehensive Evaluation of Audio Foundation Models](https://md.research.elamur.ai/free/en/papers/shi-2026-ultraeval-audio-unified-framework-comprehensive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qundong Shi, Jie Zhou, Biyuan Lin, et al.*2026 · 1 citation*
43. **[Unlocking Large Audio-Language Models for Interactive Language Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-unlocking-large-audio-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongfu Liu, Zhouying Cui, Xiangming Gu, et al.*2026 · 1 citation*
44. **[WhiteHouse: Translation of the Casablanca Corpus for Multi-dialectal Arabic Speech Translation](https://md.research.elamur.ai/free/en/papers/bougares-2026-whitehouse-translation-casablanca-corpus-multi/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Fethi Bougares, Salima Mdhaffar, Yannick Estève*2026 · 1 citation*
45. [**English Pronunciation Evaluation without Complex Joint Training: LoRA Fine-tuned Speech Multimodal LLM arXiv:2509.02915**Taekyung Ahn, Hosung Nam*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/ahn-2025-english-pronunciation-evaluation-complex-joint/)
46. **[Mispronunciation Detection Without L2 Pronunciation Dataset in Low-Resource Setting: A Case Study in Finland Swedish](https://md.research.elamur.ai/free/en/papers/phan-2025-mispronunciation-detection-l2-pronunciation-dataset/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Nhan Phan, Mikko Kuronen, Maria Kautonen, et al.*2025 · 1 citation*
47. **[AEQ-Bench: Measuring Empathy of Omni-Modal Large Models](https://md.research.elamur.ai/free/en/papers/luo-2026-aeq-bench-measuring-empathy-omni/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Luo, Lewei Yao, Lanqing Hong, et al.*2026*
48. **[Beyond Transcription: Unified Audio Schema for Perception-Aware AudioLLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-transcription-unified-audio-schema/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Linhao Zhang, Yuhan Song, Aiwei Liu, et al.*2026*
49. [**CARDAMOM: A Micro-Dialectal Arabic Speech Dataset for ASR arXiv:2609.34481**Bashar Talafha, Samar M. Magdy, Aisha Alansari, et al.*2026*](https://md.research.elamur.ai/free/en/papers/talafha-2026-cardamom-micro-dialectal-arabic-speech/)
50. **[Comprehensive Benchmarking of Long-Form Speech Generation in Diverse Scenarios](https://md.research.elamur.ai/free/en/papers/pan-2026-comprehensive-benchmarking-long-form-speech/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Changhao Pan, Rui Yang, Han Wang, et al.*2026*
51. **[DialogueSidon: Recovering Full-Duplex Dialogue Tracks from In-the-Wild Dialogue Audio](https://md.research.elamur.ai/free/en/papers/nakata-2026-dialoguesidon-recovering-full-duplex-dialogue/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Wataru Nakata, Yuki Saito, Kazuki Yamauchi, et al.*2026*
52. **[DIFFA-2: A Practical Diffusion Large Language Model for General Audio Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2026-diffa-2-practical-diffusion-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaming Zhou, Xuxin Cheng, Shiwan Zhao, et al.*2026*
53. **[Intent vs. Surface: Recovering Acoustic Realization from Modern ASR for Pronunciation Training](https://md.research.elamur.ai/free/en/papers/park-2026-intent-vs-surface-recovering-acoustic/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Seongjin Park*2026*
54. [**Multi-Task Instruction Tuning via Data Scheduling for Low-Resource Arabic SpeechLLMs arXiv:2601.12494**Hunzalah Hassan Bhatti, Firoj Alam, Shammur Absar Chowdhury*2026*](https://md.research.elamur.ai/free/en/papers/bhatti-2026-multi-task-instruction-tuning-data/)
55. **[SAUCE: Summary Analysis Using Conversation Entailment](https://md.research.elamur.ai/free/en/papers/sung-2026-sauce-summary-analysis-conversation-entailment/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Man-Ling Sung, Hemanth Kandula, Jeff Ma, et al.*2026*
56. **[Speech-Hands: A Self-Reflection Voice Agentic Approach to Speech Recognition and Audio Reasoning with Omni Perception](https://md.research.elamur.ai/free/en/papers/wan-2026-speech-hands-self-reflection-voice/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Wan, Chao-Han Huck Yang, Jinchuan Tian, et al.*2026*
57. **[Using the Mimi codec for metalinguistic representations](https://md.research.elamur.ai/free/en/papers/saloev-2026-mimi-codec-metalinguistic-representations/) [Workshop on the Bridges and Gaps between Formal and Computational Linguistics](https://md.research.elamur.ai/free/en/venues/brigap/)**Artem Saloev, Erin Pacquetet, Nicolas Ballier*2026*
58. **[Vietnamese Automatic Speech Recognition: A Revisit](https://md.research.elamur.ai/free/en/papers/vu-2026-vietnamese-automatic-speech-recognition-revisit/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Thi Vu, Linh The Nguyen, Dat Quoc Nguyen*2026*

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