Comparative analysis of the Moonshine and Faster-Whisper Tiny transcription models, focusing on latency and Word Error Rate (WER)
-
Updated
Oct 27, 2024 - Jupyter Notebook
#
jiwer
Here are 4 public repositories matching this topic...
Correcting the noisy OCR output on Bangla language using seq2seq Model
-
Updated
Jun 21, 2020 - Python
his repository contains an Automatic Speech Recognition (ASR) system for Amharic built by fine-tuning Facebook’s Wav2Vec2.0 model using Hugging Face Transformers. The goal is to provide an open-source Amharic speech-to-text model, making it easier for developers and researchers to work with Amharic audio data.
-
Updated
Aug 27, 2025 - Python
Python tool to evaluate Automatic Speech Recognition (ASR) outputs by calculating Word Error Rate (WER) for multiple models. Ideal for NLP research, ASR benchmarking, and improving transcription accuracy.
python nlp data-science speech ml speech-recognition research-project automatic-speech-recognition speech-to-text asr model-evaluation word-error-rate text-evaluation jiwer
-
Updated
Jan 24, 2026 - Python
Improve this page
Add a description, image, and links to the jiwer topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the jiwer topic, visit your repo's landing page and select "manage topics."