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None of these voices match the Cortana text-to-speech voice which can be found on Windows Phone 8.1, Windows 10, and Windows 10 Mobile. In an attempt to unify its software with Windows 10, all of Microsoft's current platforms use the same text-to-speech voices except for Microsoft David and a few others.
Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech-to-text (STT).
Deep learning speech synthesis refers to the application of deep learning models to generate natural-sounding human speech from written text (text-to-speech) or spectrum . Deep neural networks are trained using large amounts of recorded speech and, in the case of a text-to-speech system, the associated labels and/or input text.
The major steps in producing speech from text are as follows: Structure analysis: Processes the input text to determine where paragraphs, sentences, and other structures start and end. For most languages, punctuation and formatting data are used in this stage. Text pre-processing: Analyzes the input text for special constructs of the language.
Microsoft Azure, or just Azure (/ˈæʒər, ˈeɪʒər/ AZH-ər, AY-zhər, UK also /ˈæzjʊər, ˈeɪzjʊər/ AZ-ure, AY-zure), [5] [6] [7] is the cloud computing platform developed by Microsoft. It has management, access and development of applications and services to individuals, companies, and governments through its global infrastructure.
Re-captioning is used to augment training data, by using a video-to-text model to create detailed captions on videos. [ 7 ] OpenAI trained the model using publicly available videos as well as copyrighted videos licensed for the purpose, but did not reveal the number or the exact source of the videos. [ 5 ]
Text-to-speech software has been widely available for desktop computers since the 1990s, and Moore’s Law increases in CPU and memory capabilities have contributed to making their inclusion in software and hardware solutions more feasible. In the wake of these trends, text-to-speech is finding its way into everyday consumer electronics. [5]
A text-to-video model is a machine learning model that uses a natural language description as input to produce a video relevant to the input text. [1] Advancements during the 2020s in the generation of high-quality, text-conditioned videos have largely been driven by the development of video diffusion models .