Boosting Wav2Vec2 with n-grams in 🤗 Transformers

Making automatic speech recognition work on large files with Wav2Vec2 in 🤗 Transformers

Fine-Tune XLSR-Wav2Vec2 for low-resource ASR with 🤗 Transformers

Fine-Tune Wav2Vec2 for English ASR in Hugging Face with 🤗 Transformers

Fine-Tune W2V2-Bert for low-resource ASR with 🤗 Transformers

Training a language model with 🤗 Transformers using TensorFlow and TPUs

Overview of natively supported quantization schemes in 🤗 Transformers

Phonetic Error Analysis of Raw Waveform Acoustic Models

arXiv:2606. 07030v1 Announce Type: cross Abstract: We analyse error patterns of raw waveform acoustic models on TIMIT phone recognition beyond the overall phone error rate (PER).

HybridCodec: Modeling Discrete and Continuous Representations for Efficient Speech Language Models

arXiv:2606. 27627v1 Announce Type: cross Abstract: Discrete audio representations have become increasingly popular for building multimodal text-audio systems and integrating audio capabilities into Large Language Models (LLMs).

Fine-Tune Whisper For Multilingual ASR with 🤗 Transformers

UniPASE: A Generative Model for Universal Speech Enhancement with High Fidelity and Low Hallucinations

arXiv:2604. 14606v2 Announce Type: cross Abstract: Universal speech enhancement (USE) aims to restore speech signals from diverse distortions across multiple sampling rates.

How to train a new language model from scratch using Transformers and Tokenizers

ReGen: Hierarchical Multi-Prompt Representation Generation for Efficient Waveform Diffusion Models

arXiv:2607. 09134v1 Announce Type: cross Abstract: Representation alignment (REPA) has been investigated to accelerate diffusion training, but we observe that regularizing intermediate representations in diffusion Transformers (DiT) may implicitly entangle latents and limit generative capacity.