Character Error Rate
PulseAugur coverage of Character Error Rate — every cluster mentioning Character Error Rate across labs, papers, and developer communities, ranked by signal.
5 day(s) with sentiment data
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Vision-Language Models Show Subtle Hallucinations in Historical Document OCR
A new research paper analyzes the performance of vision-language models (VLMs) in transcribing historical documents, finding that while they outperform traditional optical character recognition (OCR) systems on standard…
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Whisper model fine-tuned for robust Assamese speech recognition
Researchers have developed a fine-tuned version of the Whisper model to improve Automatic Speech Recognition (ASR) for the Assamese language. The fine-tuned model, trained on the Mozilla Common Voice 24.0-Assamese corpu…
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LLMs fail to translate Korean Braille, study finds
A new research paper reveals significant accessibility failures in state-of-the-art Large Language Models (LLMs) when it comes to translating Korean Braille. Despite expectations that these models could handle Braille t…
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New RLHF framework improves Vietnamese translation of historical manuscripts
Researchers have developed a new multimodal Reinforcement Learning from Human Feedback (RLHF) framework to translate historical Han-Nom manuscripts into modern Vietnamese. This approach leverages both the visual informa…
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Qwen-ASR-1.7B adapted for multilingual two-speaker speech recognition · 2 sources tracked
Researchers have developed a system for the MLC-SLM 2026 Challenge that adapts the Qwen3-ASR-1.7B model for multilingual, two-speaker conversational speech. The system integrates a speaker diarization front end with the…
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New dataset and CRNN model advance Urdu handwritten text recognition
Researchers have introduced the Urdu Katib Handwritten Dataset (UKHD), the first offline dataset of historical Urdu handwritten text lines. This dataset aims to address the scarcity of resources for Urdu Handwritten Tex…
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New paradigm improves ASR metrics by correlating errors with human perception
Researchers have introduced a new paradigm for evaluating automatic speech recognition (ASR) systems that aims to improve upon existing metrics like Word Error Rate (WER) and Character Error Rate (CER). The proposed met…
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LLM preference optimization advances TTS accuracy and user personalization
Researchers have developed new methods for aligning large language models (LLMs) with user preferences. One approach, TKTO, focuses on text-to-speech systems, enabling data-efficient, token-level optimization to improve…