Search Results for "error" - Page 5

Blunder is an automated tool for analyzing chained exceptions in Java. It's usefull for classify, generate a customized error message and a list for possible solutions.

A voice recognition application which detect Quran (Islamic Holy book) pronunciation and result in a detection success percentage for each word of the Quran statements, when complete it can be considered a base for Arabic language recognition.

A Java implementation of wide range of black box and incremental algorithms for error/entailment explanations.

This is the source code for my 11th grade science fair project. It involves the use of autoencoders to improve error rates with small amounts of labeled data but large amounts of unlabeled data.

JKalman is an Open Source Java implementation of Kalman filter. Kalman filter is an efficient computational (recursive) tool to estimate the dynamic state of a process in a way that minimizes the mean of error.

...It was trained using Mozilla’s Common Voice 6.1 and CSS10 datasets to recognize Russian speech with high accuracy. The model operates best with audio sampled at 16kHz and can transcribe Russian speech directly without a language model. It achieves a Word Error Rate (WER) of 13.3% and Character Error Rate (CER) of 2.88% on the Common Voice test set, with even better results when used with a language model. The model supports both PyTorch and JAX and is compatible with the Hugging Face Transformers and HuggingSound libraries. It is ideal for Russian voice transcription tasks in research, accessibility, and interface development. ...

...It is based on Facebook’s wav2vec2-large-xlsr-53, a multilingual self-supervised learning model, and is optimized to transcribe Portuguese speech sampled at 16kHz. The model performs well without a language model, though adding one can improve word error rate (WER) and character error rate (CER). It achieves a WER of 11.3% (or 9.01% with LM) on Common Voice test data, demonstrating high accuracy for a single-language ASR model. Inference can be done using HuggingSound or via a custom PyTorch script using Hugging Face Transformers and Librosa. Training scripts and evaluation methods are open source and available on GitHub. ...

...Write or paste your JavaScript code in the textarea. Click the "Check Code" button to see linting results. Features Comprehensive syntax and style checking using ESLint. Detailed error messages including line numbers and descriptions. License This project is open source and available under the MIT License.

Hermes 4 405B FP8 is a cutting-edge large language model developed by Nous Research, built on Llama-3.1-405B and optimized for frontier reasoning and alignment. It introduces a hybrid reasoning mode with explicit <think> segments, enabling the model to deliberate deeply when needed and switch to faster responses when desired. Post-training improvements include a vastly expanded corpus with ~60B tokens, boosting performance across math, code, STEM, logic, creativity, and structured outputs....