Flashlight

Health v2 · maintenance only

Adoption not part of the score

5466 stars · 502 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

wav2letter++ is Facebook AI Research's end-to-end automatic speech recognition (ASR) toolkit written in C++. It has been consolidated into the Flashlight library's ASR application, with this repository serving as an archive of recipes and pre-trained models for reproducing ASR research papers.

Use cases

• train an end-to-end speech recognition model
• transcribe audio to text with a pretrained ASR model
• reproduce research papers on speech recognition
• build a streaming ConvNet speech recognizer
• run lexicon-free speech recognition

When to choose

• you need a fast C++ end-to-end ASR toolkit with pretrained models
• you want to reproduce published wav2letter/Flashlight ASR research results
• you are training ConvNet-based speech recognition models on GPU

When to avoid

• you need a Python-first ASR framework with broad ecosystem support
• you want actively developed new features, since development moved to Flashlight
• you need exact reproducibility without pinning Flashlight <= 0.3.2

Facets

library · maturity maintenance

speech-recognition machine-learning deep-learning audio-processing speech-processing machine-learning deep-learning cpp asr wav2letter end-to-end convnets pretrained-models facebook-ai-research linux macos gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="flashlight/flashlight")