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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]
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.
Speech recognition is a multi-leveled pattern recognition task. Acoustical signals are structured into a hierarchy of units, e.g. Phonemes, Words, Phrases, and Sentences; Each level provides additional constraints; e.g. Known word pronunciations or legal word sequences, which can compensate for errors or uncertainties at a lower level;
Gestalt pattern matching, [1] also Ratcliff/Obershelp pattern recognition, [2] is a string-matching algorithm for determining the similarity of two strings. It was developed in 1983 by John W. Ratcliff and John A. Obershelp and published in the Dr. Dobb's Journal in July 1988.
Speaker diarisation (or diarization) is the process of partitioning an audio stream containing human speech into homogeneous segments according to the identity of each speaker. [1] It can enhance the readability of an automatic speech transcription by structuring the audio stream into speaker turns and, when used together with speaker ...
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
[9] [10] The last two examples form the subtopic image analysis of pattern recognition that deals with digital images as input to pattern recognition systems. [11] [12] Optical character recognition is an example of the application of a pattern classifier. The method of signing one's name was captured with stylus and overlay starting in 1990.
Sphinx is a continuous-speech, speaker-independent recognition system making use of hidden Markov acoustic models and an n-gram statistical language model. It was developed by Kai-Fu Lee . Sphinx featured feasibility of continuous-speech, speaker-independent large-vocabulary recognition, the possibility of which was in dispute at the time (1986).