Search Results for "cpu-z"

whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples....

...Reduce resource demands and efficiently deploy on a range of Intel® platforms from edge to cloud. This open-source version includes several components: namely Model Optimizer, OpenVINO™ Runtime, Post-Training Optimization Tool, as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. It supports pre-trained models from the Open Model Zoo, along with 100+ open source and public models in popular formats such as TensorFlow, ONNX, PaddlePaddle, MXNet, Caffe, Kaldi.

...Features: - 100% offline (no cloud, no data sharing) - Multilingual voice commands - Control apps, browser, and system - OCR + text-to-speech screen reading - Portable (no installation) - No registry changes NVIDIA GPU recommended (GTX 1060+). CPU mode supported (slower). For any other information please contact : Ducktheapp

...Features: - 100% offline (no cloud, no data sharing) - Multilingual voice commands - Control apps, browser, and system - OCR + text-to-speech screen reading - Portable (no installation) - No registry changes NVIDIA GPU recommended (GTX 1060+). CPU mode supported (slower). A practical alternative to cloud-based voice assistants. For any other information please contact : ducktheapp@gmail.com The Duck

ASRT is an end-to-end deep-learning Chinese ASR system built with TensorFlow/Keras, using convolution + CTC and a Max-Entropy HMM language model. It provides a REST/gRPC server backend and client SDKs in multiple languages (Python, Java, Go, Windows). Notably lightweight, it performs well without needing GPU acceleration and runs across platforms, targeting developers and researchers building Chinese voice interfaces.

...Flashlight can be broken down into several components as described above. Each component can be incrementally built by specifying the correct build options. Flashlight is most-easily built and installed with vcpkg. Both the CUDA and CPU backends are supported with vcpkg. For either backend, first, install Intel MKL. Flashlight app binaries are also built for the selected features and are installed into the vcpkg install tree's tools directory.

...This repository includes recipes to reproduce the following research papers as well as pre-trained models. All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run export KENLM_ROOT_DIR=... so that wav2letter++ can find it. This is needed because KenLM doesn't support a make install step.wav2letter++ expects audio and transcription data to be prepared in a specific format so that they can be read from the pipelines. ...

Hello everyone! I am presenting a software named S.T.A.N, a voice recognition software which recognizes your voice and performs actions like from opening to facebook to renaming, copying a file, creating a folder and many more! This software has over 50+ commands to perform by just listening to your voice! so just download it and check it out. Your comments and feedback is valuable to us. And if you like, please like our facebook page and mail us!