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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).
Speech Recognition is available only in English, French, Spanish, German, Japanese, Simplified Chinese, and Traditional Chinese and only in the corresponding version of Windows; meaning you cannot use the speech recognition engine in one language if you use a version of Windows in another language.
With speech recognition technology, transcriptionists can automatically convert recordings to text transcripts by opening recordings in a PC and uploading them to a cloud for automatic transcription, or transcribe recordings in real-time by using digital dictation. Depending on quality of recordings, machine generated transcripts may still need ...
Common Voice is a crowdsourcing project started by Mozilla to create a free database for speech recognition software. The project is supported by volunteers who record sample sentences with a microphone and review recordings of other users. The transcribed sentences are collected in a voice database available under the public domain license CC0 ...
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Most voice synthesizers (including Apple's Siri) use concatenative synthesis, [5] in which a program stores individual phonemes and then pieces them together to form words and sentences. WaveNet synthesizes speech with human-like emphasis and inflection on syllables, phonemes, and words. Unlike most other text-to-speech systems, a WaveNet model ...
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It also plays an important role for several subfields of speech technology. Common examples for transcriptions outside academia are the proceedings of a court hearing such as a criminal trial (by a court reporter) or a physician's recorded voice notes (medical transcription). This article focuses on transcription in linguistics.
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