We may receive compensation when you click on links to products we review. Please view our affiliate disclosure. The rise of artificial intelligence (AI) has led to a wide range of incredible text to ...

In this notebook, you will build a deep neural network that functions as part of an end-to-end automatic speech recognition (ASR ... networks that can map these audio features to transcribed text.

The project uses speech data and their corresponding transcriptions to train a deep learning model that can be used to collect Swahili speech data and store it's corresponding text. Since speech data ...

We list the best text-to-speech software, to make it simple and easy to convert text to voice for either accessibility or productivity purposes. Finding the best text-to-speech software is key for ...

Those of us who were around in the late 70s and into the 80s might remember the Speak & Spell, a children’s toy with a remarkable text-to-speech synthesizer. While it sounds dated by today’s ...

The study employed two deep-learning models ... The second was OpenAI's text-embedding-ada-002 model, which was utilized to process linguistic features by converting speech transcripts into ...

Abstract: Grammar correction in spoken English can enhance proficiency. This paper briefly introduces the gate recurrent unit (GRU) algorithm and its application in ...

Natural language processing applications have moved beyond basic translators and speech-to-text ... service which uses deep learning to derive meaning from unstructured text data.