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Code-excited linear prediction (CELP) is a linear predictive speech coding algorithm originally proposed by Manfred R. Schroeder and Bishnu S. Atal in 1985. At the time, it provided significantly better quality than existing low bit-rate algorithms, such as residual-excited linear prediction (RELP) and linear predictive coding (LPC) vocoders (e.g., FS-1015).
The T5 encoder can be used as a text encoder, much like BERT. It encodes a text into a sequence of real-number vectors, which can be used for downstream applications. For example, Google Imagen [ 26 ] uses T5-XXL as text encoder, and the encoded text vectors are used as conditioning on a diffusion model .
The use of speech recognition is more naturally suited to the generation of narrative text, as part of a radiology/pathology interpretation, progress note or discharge summary: the ergonomic gains of using speech recognition to enter structured discrete data (e.g., numeric values or codes from a list or a controlled vocabulary) are relatively ...
Linear predictive coding (LPC) is a method used mostly in audio signal processing and speech processing for representing the spectral envelope of a digital signal of speech in compressed form, using the information of a linear predictive model. [1] [2] LPC is the most widely used method in speech coding and speech synthesis.
The speaker encoders then become part of the neural text-to-speech models, so that it can determine the style and characteristics of the output speech. This procedure has shown the community that it is possible to use only a single model to generate speech with multiple styles.
TMS5100 (TMC0281, internal TI name is '0280' hence chip is sometimes labeled TMC0280): First LPC speech chip. Used a custom 4-bit serial interface using TMS6100 or TMS6125 mask ROM ICs; used on all non-super versions of the Speak & Spell [7] [8] except for the 1980 UK version, which used the TMC0280/CD2801 below. [9] Publicly sold as TMS5100.
OpenAI claims that the combination of different training data used in its development has led to improved recognition of accents, background noise and jargon compared to previous approaches. [3] Whisper is a weakly-supervised deep learning acoustic model, made using an encoder-decoder transformer architecture. [1]
Early 1970s vocoder, custom-built for electronic music band Kraftwerk. A vocoder (/ ˈ v oʊ k oʊ d ər /, a portmanteau of voice and encoder) is a category of speech coding that analyzes and synthesizes the human voice signal for audio data compression, multiplexing, voice encryption or voice transformation.