---
title: "Who cites Transformer-Based Multi-Aspect — 11 citing papers"
description: "11 papers of the Elamur Research library cite «Transformer-Based Multi-Aspect Multi-Granularity Non-Native English Speaker Pronunciation…"
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---
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# Who cites «Transformer-Based Multi-Aspect Multi-Granularity Non-Native English Speaker Pronunciation Assessment»

11 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «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/)

1. **[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*
2. **[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*
3. **[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*
4. [**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/)
5. [**Automated detection of pronunciation errors in non-native English speech employing deep learning arXiv:2209.06265**Daniel Korzekwa*2022 · 1 citation*](https://md.research.elamur.ai/free/en/papers/korzekwa-2022-automated-detection-pronunciation-errors-non/)
6. **[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*

5 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/gong-2022-transformer-based-multi-aspect-multi/) — Transformer-Based Multi-Aspect Multi-Granularity Non-Native English Speaker Pronunciation Assessment