NDLI: A comparison of fitness functions in a genetic algorithm for acoustic-articulatory parameter inversion of vowels

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A comparison of fitness functions in a genetic algorithm for acoustic-articulatory parameter inversion of vowels

Content Provider	ACM Digital Library
Author	Miranda, Eduardo Kirke, Alexis Drayton, Jared
Abstract	Articulatory speech synthesis provides an alternative to the state of the art concatenative and formant systems, holding potential for more versatile and expressive artificial speech due to its physical modelling basis. However, a major limitation of practical articulatory synthesis is gaining adequate control of the complex underlying physical models, which stems from a lack of articulatory data. In an effort to procure more data, a Genetic Algorithm approach to Acoustic-Articulatory Parameter Inversion is taken. This paper presents the initial results from testing a number of fitness functions for the Acoustic-Articulatory Parameter Inversion of three vowels, /a/, /o/, and /e/. Three feature vector representations of the vowels were tested; Hertz, Mel-scale, and Cents, in conjunction with three distance metrics. The distance metrics defined the fitness score by calculating the similarity between a candidate and targets feature vector. A Voiced/Un-Voiced constraint was also added as a penalty function, and an indicator of loudness was implemented using a Root Mean Square based co-efficient. The results indicated that certain combinations of the above could lead to convergence towards all three vowels. However, the quality of convergence was not uniform.
Starting Page	271
Ending Page	272
Page Count	2
File Format	PDF
ISBN	9781450349390
DOI	10.1145/3067695.3076112
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-07-15
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Genetic algorithm Physical modelling Speech synthesis
Content Type	Text
Resource Type	Article

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