mlsanityData to 14 Oct 2026

wav2letter++: The Fastest Open-source Speech Recognition System

arXiv 1812.07625 ↗First posted 18 Dec 2018cs.CLcited by 42

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Abstract (arXiv)

This paper introduces wav2letter++, the fastest open-source deep learning speech recognition framework. wav2letter++ is written entirely in C++, and uses the ArrayFire tensor library for maximum efficiency. Here we explain the architecture and design of the wav2letter++ system and compare it to other major open-source speech recognition systems. In some cases wav2letter++ is more than 2x faster than other optimized frameworks for training end-to-end neural networks for speech recognition. We also show that wav2letter++'s training times scale linearly to 64 GPUs, the highest we tested, for models with 100 million parameters. High-performance frameworks enable fast iteration, which is often a crucial factor in successful research and model tuning on new datasets and tasks.

Key facts. Cited by 42 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Dec 2018.

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Citing papers per year: 2021: 18; 2022: 11; 2023: 6; 2024: 3; 2025: 3; 2026: 1.

42 papers.

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  1. 2021WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processingcited by 1,657
  2. 2021SUPERB: Speech processing Universal PERformance Benchmarkcited by 666
  3. 2021VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretationcited by 463
  4. 2023Scaling Speech Technology to 1,000+ Languagescited by 411
  5. 2021Robust wav2vec 2.0: Analyzing Domain Shift in Self-Supervised Pre-Trainingcited by 151
  6. 2021Unsupervised Speech Recognitioncited by 148
  7. 2021Simple and Effective Zero-shot Cross-lingual Phoneme Recognitioncited by 79
  8. 2021Towards Building ASR Systems for the Next Billion Userscited by 47
  9. 2022Wav2Seq: Pre-training Speech-to-Text Encoder-Decoder Models Using Pseudo Languagescited by 26
  10. 2022On Neural Architecture Inductive Biases for Relational Taskscited by 26
  11. 2022Flashlight: Enabling Innovation in Tools for Machine Learningcited by 25
  12. 2022SPIRAL: Self-supervised Perturbation-Invariant Representation Learning for Speech Pre-Trainingcited by 19
30 more
  1. 2024emg2qwerty: A Large Dataset with Baselines for Touch Typing using Surface Electromyographycited by 18
  2. 2022Supervision-Guided Codebooks for Masked Prediction in Speech Pre-trainingcited by 14
  3. 2021Assem-VC: Realistic Voice Conversion by Assembling Modern Speech Synthesis Techniquescited by 11
  4. 2022Star Temporal Classification: Sequence Classification with Partially Labeled Datacited by 10
  5. 2022On-demand compute reduction with stochastic wav2vec 2.0cited by 10
  6. 2021What do End-to-End Speech Models Learn about Speaker, Language and Channel Information? A Layer-wise and Neuron-level Analysiscited by 9
  7. 2022Wav2Vec-Aug: Improved self-supervised training with limited datacited by 9
  8. 2024Scaling A Simple Approach to Zero-Shot Speech Recognitioncited by 8
  9. 2021ATCSpeechNet: A multilingual end-to-end speech recognition framework for air traffic control systemscited by 6
  10. 2021Comparing CTC and LFMMI for out-of-domain adaptation of wav2vec 2.0 acoustic modelcited by 6
  11. 2022Text-To-Speech Data Augmentation for Low Resource Speech Recognitioncited by 6
  12. 2023Improving Medical Speech-to-Text Accuracy with Vision-Language Pre-training Modelcited by 6
  13. 2021Audiomer: A Convolutional Transformer For Keyword Spottingcited by 4
  14. 2022Huqariq: A Multilingual Speech Corpus of Native Languages of Peru for Speech Recognitioncited by 4
  15. 2023Evaluating OpenAI's Whisper ASR for Punctuation Prediction and Topic Modeling of life histories of the Museum of the Personcited by 4
  16. 2025TS-SUPERB: A Target Speech Processing Benchmark for Speech Self-Supervised Learning Modelscited by 4
  17. 2021Are E2E ASR models ready for an industrial usage?cited by 3
  18. 2021A Comparison of Methods for OOV-word Recognition on a New Public Datasetcited by 2
  19. 2021Word Order Does Not Matter For Speech Recognitioncited by 2
  20. 2021Influence of ASR and Language Model on Alzheimer's Disease Detectioncited by 2
  21. 2021Speech recognition for air traffic control via feature learning and end-to-end trainingcited by 2
  22. 2023Language-universal phonetic encoder for low-resource speech recognitioncited by 2
  23. 2023Don't Stop Self-Supervision: Accent Adaptation of Speech Representations via Residual Adapterscited by 2
  24. 2021General-Purpose Speech Representation Learning through a Self-Supervised Multi-Granularity Frameworkcited by 1
  25. 2023InterFormer: Interactive Local and Global Features Fusion for Automatic Speech Recognitioncited by 1
  26. 2024Deep Learning Models in Speech Recognition: Measuring GPU Energy Consumption, Impact of Noise and Model Quantization for Edge Deploymentcited by 1
  27. 2022Learning Invariant Representation and Risk Minimized for Unsupervised Accent Domain Adaptationcited by 0
  28. 2025Enhancing Aviation Communication Transcription: Fine-Tuning Distil-Whisper with LoRAcited by 0
  29. 2025Learning Speech Representations with Variational Predictive Codingcited by 0
  30. 2026Giving Voice to the Constitution: Low-Resource Text-to-Speech for Quechua and Spanish Using a Bilingual Legal Corpuscited by 0