What are the potential societal impacts of highly accurate Deep Speech technology?

trained on clean speech signals as a deep speech model for speech enhancement [10]–[13]. In a semi-supervised speech separation method called multichannel ... Dec 5, 2019 ... DeepSpeech is a deep learning-based ASR engine with a simple API. We also provide pre-trained English models. Our latest release, version v0.6, offers the ... Jun 21, 2020 ... Top 15 Open Source Speech Recognition/TTS/STT/ Systems. There has been many open source speech recognition, TTS, STT and ASR libraries developed ... We show that an end-to-end deep learning approach can be used to recognize either English or Mandarin Chinese speech--two vastly different languages. Connected Speech Agreement Criterion; Qualification level: B Additional information; Completion time: Diagnostic Screen 5 minutes; Articulation assessment 10 ... Oct 31, 2017 ... Along this endeavor we developed Deep Speech 1 as a proof-of-concept to show a simple model can be highly competitive with state-of-art models. Oct 13, 2021 ... This function will have three parameters: the DeepSpeech object (returned from load_models), the audio file, and fs the sampling rate of the ... In this investigation, a deep neural network (DNN) based speech extraction method is proposed to enhance a speech signal propagating from the desired direction. DeepSpeech is a tool for automatically transcribing spoken audio. DeepSpeech takes digital audio as input and returns a “most likely” text transcript of that ... 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 ...