Showing 441 open source projects for "automatic"

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  • 1
    RL HNFP is a neuro Fuzzy model which can automatic generate set of rule. So it can implement in domain although human don't have knowledge on it. This project implement that algorithm in Java so other people can use that for their application
    Downloads: 0 This Week
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  • 2
    A tool for segmenting objects of interest in images, namely creating masks, and storing them for a set of images. It may provide some automatic/interactive segmentation for certain classes of objects. For computer vision / machine learning applications.
    Downloads: 0 This Week
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  • 3
    The Infomap NLP software performs automatic indexing of words and documents from free-text corpora, using a variant of LSA to enable information retrieval and other applications. It was developed by the Infomap Project at Stanford University's CSLI.
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    Downloads: 1 This Week
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  • 4
    Voice XML Enabling Software (VXES) is an application that connects a VoiceXML Interpreter, a telephony platform, and MRCP servers that provide services for Automatic Speech Recognition and Text to Speech Synthesis. C++, Windows & Linux OS supported
    Downloads: 0 This Week
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  • 5
    Evomusic deals with automatic composition of music (midi-files) using evolutionary algorithms. Currently we are testing multiple approaches for doing this successfully, especially neural networks and/or algorithms based on simple music theory.
    Downloads: 0 This Week
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  • 6
    FLPD is an automatic learning system based on fuzzy prototypes, composed of a C++ library for machine learning and fuzzy logic and an experimentation framework.
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  • 7
    "GUI" for DCTC (Direct Connect Text Client) focused on fully automatic run on servers, gathering upload stats and working as a chat bot. It's modular design enables simple extending its functionality.
    Downloads: 3 This Week
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  • 8
    The TreeQ package is a set of C-language applications that implement a automatic machine learning algorithm based on a tree-structured classifier. This approach is particularly effective for high-dimensional continuous data such as audio and video.
    Downloads: 0 This Week
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  • 9
    Prawda is open source (semi-)automatic human language translation system. It analyses each sentence of the text and suggests variants of its translation. Several languages and translation directions are supported.
    Downloads: 0 This Week
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  • 10
    GACS (Genetic Algorithm Class Scheduler) aims to provide to academic institutions an efficient and automatic way to generate their time scheduling for the classes that will be imparted in an academic period.
    Downloads: 2 This Week
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  • 11
    The project is aimed at automatic target following using a camera , a computer vision system and a microcontroller that moves the cam. The project should mainly work under linux and it might be ported into windows,
    Downloads: 0 This Week
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  • 12
    BLEURT-20-D12

    BLEURT-20-D12

    Custom BLEURT model for evaluating text similarity using PyTorch

    BLEURT-20-D12 is a PyTorch implementation of BLEURT, a model designed to assess the semantic similarity between two text sequences. It serves as an automatic evaluation metric for natural language generation tasks like summarization and translation. The model predicts a score indicating how similar a candidate sentence is to a reference sentence, with higher scores indicating greater semantic overlap. Unlike standard BLEURT models from TensorFlow, this version is built from a custom PyTorch transformer library. ...
    Downloads: 0 This Week
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  • 13
    wav2vec2-large-xlsr-53-portuguese

    wav2vec2-large-xlsr-53-portuguese

    Portuguese ASR model fine-tuned on XLSR-53 for 16kHz audio input

    wav2vec2-large-xlsr-53-portuguese is an automatic speech recognition (ASR) model fine-tuned on Portuguese using the Common Voice 6.1 dataset. 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).
    Downloads: 0 This Week
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  • 14

    automated-linguistic-analysis

    Automated Linguistic Analysis, with both monolith and cluster versions

    Sample application showcasing usage of technologies such as: * OSGi R7 Promises for asynchronous generation of transcriptions and linguistic analyses * OSGi R7 Push Stream and JAX RS Server Sent Events for push notifications of processing status * Apache Camel 2.23.1 and RabbitMQ 3.7 for asynchronous communication between services * JPA 2.1 and Hibernate 5.2.12, along with OSGi R7 JPA and Transaction Control services, for persistence layer * OSGi R7 HTTP and JAX RS Whiteboard for registering servlets, resources and REST controllers * OSGi R7 Configurator, Configuration Admin and Metatype services for automatic configuration of components * OSGi R7 Declarative Services for dependency injection * Maven automated build of Docker images * Maven automated deployment into Kubernetes cluster * RabbitMQ message broker as a StatefulSet * CockroachDB relational database as a StatefulSet See 'Code' tab for detailed information
    Downloads: 0 This Week
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  • 15
    granite-timeseries-ttm-r2

    granite-timeseries-ttm-r2

    Tiny pre-trained IBM model for multivariate time series forecasting

    granite-timeseries-ttm-r2 is part of IBM’s TinyTimeMixers (TTM) series—compact, pre-trained models for multivariate time series forecasting. Unlike massive foundation models, TTM models are designed to be lightweight yet powerful, with only ~805K parameters, enabling high performance even on CPU or single-GPU machines. The r2 version is pre-trained on ~700M samples (r2.1 expands to ~1B), delivering up to 15% better accuracy than the r1 version. TTM supports both zero-shot and fine-tuned...
    Downloads: 0 This Week
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  • 16
    wav2vec2-large-xlsr-53-russian

    wav2vec2-large-xlsr-53-russian

    Russian ASR model fine-tuned on Common Voice and CSS10 datasets

    wav2vec2-large-xlsr-53-russian is a fine-tuned automatic speech recognition (ASR) model based on Facebook’s wav2vec2-large-xlsr-53 and optimized for Russian. 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.
    Downloads: 0 This Week
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