An open source embedded speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers

DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu’s Deep Speech research paper. Project DeepSpeech uses Google’s TensorFlow to make the implementation easier. Documentation for installation, usage, and training models are available on deepspeech.readthedocs.io. For the latest release, including pre-trained models and checkpoints, see the latest release on GitHub. For contribution guidelines, see CONTRIBUTING.rst. For contact and support information, see SUPPORT.rst. GitHub https://github.com/mozilla/DeepSpeech    

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Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge

This is an implementation of the paper, along with the pipeline and pretrained model using an open dataset. Audio samples of the paper is available here. This open pipeline uses the Databaker dataset. Please refer to our previous pipeline for dataset preprocessing, while only the Databaker dataset is used. Besides, you need to run lexicon/build_databaker.py to build the vocabulary, download the lexicon from zdic.net, and encode them with XLM-R. Feel free to change the target directory to save the data, […]

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Chimera: Learning Shared Semantic Space for Speech-to-Text Translation

This is a Pytorch implementation for the “Chimera” paper Learning Shared Semantic Space for Speech-to-Text Translation https://arxiv.org/abs/2105.03095 (accepted by ACL Findings 2021), which aims to bridge the modality gap by unifying the task of MT (textual Machine Translation) and ST (Speech-to-Text Translation). It has achieved new SOTA performance on all 8 language pairs in MuST-C benchmark, by utilizing an external MT corpus. ![](https://github.com/Glaciohound/Chimera-ST/raw/main/chimera/resources/figs/method.png =100%x) This repository is up to now a nightly version, and is bug-prone because of code refactoring. […]

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