How are self-supervised learning techniques impacting the training of Deep Speech models?

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. Dec 1, 2020 ... Both Deep Speech and LAS, are recurrent neural network (RNN) based architectures with different approaches to modeling speech recognition. Deep ... Jun 9, 2011 ... It could be guttural or lyrical. It might be a whispered language with no body/facial movement by virtue of being in an underground environment. Jul 31, 2021 ... Hi guys, recently, I created a simple implementation of Deep Speech in Unity. But I somehow is unable to successfully use the deep speech ... Nov 29, 2017 ... These challenges inspired us to launch Project DeepSpeech and Project Common Voice. Today, we have reached two important milestones in these ... We propose a time-domain articulatory synthesis methodology and demonstrate its efficacy with both electromagnetic articulography (EMA) and synthetic ... Dec 31, 2021 ... Automatically derived deep speech parameters from the semantic verbal fluency (SVF) can potentially have an additional value to differentiate SCI, MCI and ... Dec 17, 2014 ... Our system, called Deep Speech, outperforms previously published results on the widely studied Switchboard Hub5'00, achieving 16.0% error on the ... Dec 8, 2019 ... Mozilla DeepSpeech is a speech-to-text engine powered by TensorFlow for machine learning and derived from Baidu's Deep Speech research paper. Jun 11, 2022 ... Background. Speech is the most common modality through which language is communicated, and delayed, disordered, or absent speech production is a ...