Articulation and Intelligibility by Jont B. Allen

By Jont B. Allen

This lecture is a evaluate of what's identified approximately modeling human speech reputation (HSR). A version is proposed, and knowledge are validated opposed to the version.

There appear to be a great number of theories, or issues of view, on how human speech attractiveness features, but few of those theories are accomplished. what's wanted is a collection of types which are supported through experimental remark, that signify how human speech popularity particularly works. eventually there's the sensible challenge of establishing a computing device recognizer. a method to do that is to construct a desktop recognizer in response to the reversed engineering of human acceptance. This has no longer been the normal method of automated speech acceptance (ASR).

What is required is a few perception into why this huge distinction among human functionality and today's computing device functionality exists. writer Jont Allen addresses this and different questions.

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By using log-log coordinates the k factor shows up as a change in slope. If the lines are straight, as they are up to H = 4, the k factor explains the data. The model works approximately for H ≤ 7. , intelligibility) likely played an important role in those cases. A second context result is for the case of the digits, as shown in Fig. 10. 5, as discussed in the figure caption. One thing these collective results do not tell us is how humans process the speech signal events to extract events. The first quantitative insight into that problem was provided by Miller and Nicely (1955).

21) When articulation errors are multiplied, he views the situation as describing a mapping from “no context → context,” which requires what he calls a “k-factor” as in Eq. 19). 1. 4 MILLER ET AL. CIRCA 1947–2001 In this section we shall deal with the important issues of entropy and chance, plus some restricted issues regarding context. George A. Miller was the first to explore the use of information theory in both HSR and human language processing (HLP). Miller and his colleagues raised and clarified these issues in some key speech papers.

Miller was the first to explore the use of information theory in both HSR and human language processing (HLP). Miller and his colleagues raised and clarified these issues in some key speech papers. In one classic study Miller was the first to use closed-sets to control the entropy of the listening task. By doing this, it was possible to study the importance of chance as an independent variable. In a second classic study, he quantified the error patterns of the HSR channel, by measuring the confusion matrix for consonants.

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