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JACIII Vol.16 No.2 pp. 327-334
doi: 10.20965/jaciii.2012.p0327
(2012)

Paper:

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Optimizing HMM Speech Synthesis for Low-Resource Devices

Bálint Tóth and Géza Németh

Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Magyar tudósok krt. 2, Budapest 1117, Hungary

Received:
September 15, 2011
Accepted:
November 15, 2011
Published:
March 20, 2012
Creative Commons License
Keywords:
text-to-speech, speech synthesis, hidden Markov model, mobile devices, low resource devices
Abstract
Speech synthesis can be an importantmodality in Cognitive Infocommunications (CogInfoCom). Speech output is beneficial when the visual output of a system is blocked or is difficult to reach. Extra information can be added to output by applying different voice characteristics and emotional speech. CogInfo-Com systems can use low-resource devices in many cases. This paper describes the application of Hidden Markov Model (HMM) based speech synthesis to such systems. Several optimization steps, e.g., changing HMM parameters, applying performance-specific programming methods, are analyzed on three different smartphones in terms of speed, footprint size, and subjective speech quality. The goal is to approach realtime functionality while keeping the speech quality as high as possible. Successful optimization steps and resource-dependent optimal settings are introduced.
Cite this article as:
B. Tóth and G. Németh, “Optimizing HMM Speech Synthesis for Low-Resource Devices,” J. Adv. Comput. Intell. Intell. Inform., Vol.16 No.2, pp. 327-334, 2012.
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