mlsanityData to 14 Oct 2026

Voxlect: A Speech Foundation Model Benchmark for Modeling Dialects and Regional Languages Around the Globe

arXiv 2508.01691 ↗First posted 3 Aug 2025cs.SD cs.CL eess.AScited by 5

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Abstract (arXiv)

We present Voxlect, a novel benchmark for modeling dialects and regional languages worldwide using speech foundation models. Specifically, we report comprehensive benchmark evaluations on dialects and regional language varieties in English, Arabic, Mandarin and Cantonese, Tibetan, Indic languages, Thai, Spanish, French, German, Brazilian Portuguese, and Italian. Our study used over 2 million training utterances from 30 publicly available speech corpora that are provided with dialectal information. We evaluate the performance of several widely used speech foundation models in classifying speech dialects. We assess the robustness of the dialectal models under noisy conditions and present an error analysis that highlights modeling results aligned with geographic continuity. In addition to benchmarking dialect classification, we demonstrate several downstream applications enabled by Voxlect. Specifically, we show that Voxlect can be applied to augment existing speech recognition datasets with dialect information, enabling a more detailed analysis of ASR performance across dialectal variations. Voxlect is also used as a tool to evaluate the performance of speech generation systems. Voxlect is publicly available with the license of the RAIL family at: https://github.com/tiantiaf0627/voxlect.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 22 of its 45 references that are in the map. First posted on arXiv 3 Aug 2025.

Builds on

22 of 45 references.

References · 22

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  2. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
  3. 2021WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processingcited by 1,657
  4. 2019Common Voice: A Massively-Multilingual Speech Corpuscited by 1,384
  5. 2021VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretationcited by 463
  6. 2023Scaling Speech Technology to 1,000+ Languagescited by 411
  7. 2024CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Modelscited by 288
  8. 2021Emotion Recognition from Speech Using Wav2vec 2.0 Embeddingscited by 162
  9. 2024WavLLM: Towards Robust and Adaptive Speech Large Language Modelcited by 109
  10. 2024IndicVoices: Towards building an Inclusive Multilingual Speech Dataset for Indian Languagescited by 41
  11. 2023The Edinburgh International Accents of English Corpus: Towards the Democratization of English ASRcited by 36
  12. 2024GLOBE: A High-quality English Corpus with Global Accents for Zero-shot Speaker Adaptive Text-to-Speechcited by 30
10 more
  1. 2024Towards measuring fairness in speech recognition: Fair-Speech datasetcited by 26
  2. 2023CommonAccent: Exploring Large Acoustic Pretrained Models for Accent Classification Based on Common Voicecited by 20
  3. 2025Scaling Rich Style-Prompted Text-to-Speech Datasetscited by 19
  4. 2023PEFT-SER: On the Use of Parameter Efficient Transfer Learning Approaches For Speech Emotion Recognition Using Pre-trained Speech Modelscited by 17
  5. 2023On the Robustness of Arabic Speech Dialect Identificationcited by 13
  6. 2023ITALIC: An Italian Intent Classification Datasetcited by 10
  7. 2024AccentBox: Towards High-Fidelity Zero-Shot Accent Generationcited by 9
  8. 2024USAT: A Universal Speaker-Adaptive Text-to-Speech Approachcited by 6
  9. 2024Self-supervised Speech Representations Still Struggle with African American Vernacular Englishcited by 6
  10. 2025MIKU-PAL: An Automated and Standardized Multi-Modal Method for Speech Paralinguistic and Affect Labelingcited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 4.

5 papers.

  1. 2026GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Taskscited by 14
  2. 2026Accent Vector: Controllable Accent Manipulation for Multilingual TTS Without Accented Datacited by 2
  3. 2026Towards Comprehensive Semantic Speech Embeddings for Chinese Dialectscited by 1
  4. 2025Style Amnesia: Investigating Speaking Style Degradation and Mitigation in Multi-Turn Spoken Language Modelscited by 0
  5. 2026textitVersteasch du mi? Computational and Socio-Linguistic Perspectives on GenAI, LLMs, and Non-Standard Languagecited by 0