wer

Evaluate your speech-to-text system with similarity measures such as word error rate (WER)

MeetEval - A meeting transcription evaluation toolkit

한국어 STT 출력의 CER, WER, CRR, 키워드·개체명·코퍼스 평가를 제공하는 Python 패키지

Streaming speech recognition toolkit: log-mel features, CTC greedy and prefix-beam decoding, transducer-style frame-synchronous emission, forced alignment, Chinese/English CER-WER metrics, and a chunked streaming pipeline with latency accounting. NumPy core with a CPU-only torch extra; trainable demos on synthetic audio, fully offline.

🐍📦 Ultra-fast Python package for calculating and analyzing the Word Error Rate (WER). Built for the scalable evaluation of speech and transcription accuracy.

A lightweight library for normalizing speech transcripts before computing WER

Calculates the word error rate of two strings, and the result is written into beautify HTML.

Machine Translation (MT) Evaluation Scripts

🐍📦 Easy-to-use Python package for lightning-fast Word Error Rate (WER) analysis

WER распознавания русской речи по трём доменам: Whisper large-v3-turbo, GigaAM v3, Deepgram Nova-2/Nova-3. Ранжирование движков переворачивается между доменами; сырые транскрипты опубликованы

pytest for voice agents — open-source testing and observability for voice AI. Simulate real callers over real audio, measure exact WER against known ground truth, and attribute every failure to STT, LLM, or TTS. Self-hosted, Apache-2.0.

A simple Python package to calculate word error rate (WER).

Lightweight ASR evaluation harness for measuring Word Error Rate, character accuracy, and inference latency across Whisper and other speech recognition models.

Exploring the functionality of the werpy Python package through testing within the Gradio tool for interactive user interface development.

Reproducible evaluation for voice agents: replay scoring, scripted live probes over WebSocket, and CI gates for WER, latency, barge-in behavior and task outcomes.

ASR scoring and annotation QA toolkit for researchers

Reproducible speech language model evaluation with audio-text datasets, replay and HTTP adapters, lexical metrics, streaming timelines and local reports.

Reproducible benchmark for Whisper transcription accuracy on Indian-accented English, scored per accent with Indian-English text normalization.

A standalone tool for evaluating Automatic Speech Recognition (ASR) models, particularly optimized for medical/clinical speech recognition, using Word Error Rate (WER) metric

Reproducible WER harness for speech-to-text services. Real ground truth from YouTube creator captions, WAV vs Opus comparison, SNR-calibrated noise, bootstrap CI gating.