Search Results for "gperftools-2.1-2 source code"

Omnilingual-ASR is a research codebase exploring automatic speech recognition that generalizes across a very large number of languages using shared modeling and training recipes. It focuses on leveraging self-supervised audio pretraining and scalable fine-tuning so low-resource languages can benefit from high-resource data. The project provides data preparation pipelines, training scripts, decoding utilities, and evaluation tools so researchers can reproduce results and extend to new...

Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and...

Tensorpack is a neural network training interface based on TensorFlow v1. Uses TensorFlow in the efficient way with no extra overhead. On common CNNs, it runs training 1.2~5x faster than the equivalent Keras code. Your training can probably gets faster if written with Tensorpack. Scalable data-parallel multi-GPU / distributed training strategy is off-the-shelf to use. Squeeze the best data loading performance of Python with tensorpack.dataflow. Symbolic programming (e.g. tf.data) does not...

The input pipeline must be prepared by the users. This code is aimed to provide the implementation for Coupled 3D Convolutional Neural Networks for audio-visual matching. Lip-reading can be a specific application for this work. Audio-visual recognition (AVR) has been considered as a solution for speech recognition tasks when the audio is corrupted, as well as a visual recognition method used for speaker verification in multi-speaker scenarios. The approach of AVR systems is to leverage the...

This product recognizes oral commands and translates them to domotic orders for a domotic system. This product does not implement a domotic system. This product is an interface to be plugged to a domotic system. The speech recognition is done by an arduino UNO board and an EasyVR shield. Available oral commands are generated from a house description file in XML format. The oral commands have to be trained for a specific users. For this purpose 2 interfaces are provided: a command line...

GoMad is a speech recognition system that allows you to control windows-based applications using your voice as input, instead of your mouse and keyboard.

Provides a voice interface for applications via a plug in system. Allows the inclusion of voice recognition in an application with a minimum of effort.