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According to the source-filter theory of the speech production [1], voiced speech is represented as the response of the vocal tract filter to the glottal voice source.
Thus, the speech is represented by 9×15=135-D feature vectors which are computed every 2.5 ms. With b=1.0183×(24.7+Fc/9.265) and n=4, this yields band-pass filters with equivalent rectangular bandwidth equal to 1 [27].
The analog spectrotemporal information in speech is represented in HG and surrounding auditory cortex and is mapped onto linguistically relevant abstract representations (i.e., phoneme codes) downstream, allowing for efficient retrieval of lexical semantic information by still higher-order areas.
While hierarchical organization of auditory and speech networks has been suggested previously (Wessinger et al. 2001; Davis and Johnsrude 2003; Okada et al. 2010; Peelle et al. 2010; Evans, Kyong et al. 2014), our RSA analyses extend these findings by determining the degree of abstraction with which speech is represented within these networks.
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The need for freedom of speech was represented in concerns over the potential loss of political freedoms.
The mapping is easy to find if the distributions of clean and observed speech are represented by inverse cumulative distribution functions (ICDF) [21, 25].
Toda et al. [9] proposed eigen-voice GMM (EV-GMM) for many-to-many VC in which the source and target speech are represented by a super vector of the reference speakers.
The actual forms of the speeches vary; in some cases only notes have been preserved, although most speeches are represented by typed, final copies.
There was the issue of language and speech (which is represented in "Einstein" by the use of repetitive texts); there was his distant mother (represented by Moran, who for part of the show sits in a high chair, away from the other actors); and there was a significant black presence (represented by Davis, in the current show).
The speech signal is represented by a source/filter model which captures only voiced speech, and where the filter bases are trained on a database of individual phonemes, resulting in a small dictionary of phoneme envelopes.
A quality measure of the proposal algorithm for four speech signals is represented in Table 2.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com