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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).
Whisper is a machine learning model for speech recognition and transcription, created by OpenAI and first released as open-source software in September 2022. [2]It is capable of transcribing speech in English and several other languages, and is also capable of translating several non-English languages into English. [1]
Tazti – Create speech command profiles to play PC games and control applications – programs. Create speech commands to open files, folders, webpages, applications. Windows 7, Windows 8 and Windows 8.1 versions. [5] Voice Finger – software that improves the Windows speech recognition system by adding several extensions to it. The software ...
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 ...
ELAN is computer software, a professional tool to manually and semi-automatically annotate and transcribe audio or video recordings. [2] It has a tier-based data model that supports multi-level, multi-participant annotation of time-based media.
IBM ViaVoice was a range of language-specific continuous speech recognition software products offered by IBM. The current version is designed primarily for use in embedded devices. The latest stable version of IBM Via Voice was 9.0 and was able to transfer text directly into Microsoft Word.
Each speaker recognition system has two phases: enrollment and verification. During enrollment, the speaker's voice is recorded and typically a number of features are extracted to form a voice print, template, or model. In the verification phase, a speech sample or "utterance" is compared against a previously created voice print.
Modular Audio Recognition Framework (MARF) is an open-source research platform and a collection of voice, sound, speech, text and natural language processing (NLP) algorithms written in Java and arranged into a modular and extensible framework that attempts to facilitate addition of new algorithms.
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