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A Praat-Based Algorithm to Extract the Amplitude Envelope and Temporal Fine Structure Using the Hilbert Transform


He, Lei; Dellwo, Volker (2016). A Praat-Based Algorithm to Extract the Amplitude Envelope and Temporal Fine Structure Using the Hilbert Transform. In: INTERSPEECH 2016, San Francisco, 8 September 2016 - 12 September 2016, 530-534.

Abstract

A speech signal can be viewed as a high frequency carrier signal containing the temporal fine structure (TFS) that is modulated by a low frequency envelope (ENV). A widely used method to decompose a speech signal into the TFS and ENV is the Hilbert transform. Although this method has been available for about one century and is widely applied in various kinds of speech processing tasks (e.g. speech chimeras), there are only very few speech processing packages that contain readily available functions for the Hilbert transform, and there is very little textbook type literature tailored for speech scientists to explain the processes behind the transform. With this paper we provide the code for carrying out the Hilbert operation to obtain the TFS and ENV in the widely used speech processing software Praat, and explain the basics of the procedure. To verify our code, we compare the Hilbert transform in Praat with a widely applied function for the same purpose in MATLAB (“hilbert(...)”). We can confirm that both methods arrive at identical outputs.

Abstract

A speech signal can be viewed as a high frequency carrier signal containing the temporal fine structure (TFS) that is modulated by a low frequency envelope (ENV). A widely used method to decompose a speech signal into the TFS and ENV is the Hilbert transform. Although this method has been available for about one century and is widely applied in various kinds of speech processing tasks (e.g. speech chimeras), there are only very few speech processing packages that contain readily available functions for the Hilbert transform, and there is very little textbook type literature tailored for speech scientists to explain the processes behind the transform. With this paper we provide the code for carrying out the Hilbert operation to obtain the TFS and ENV in the widely used speech processing software Praat, and explain the basics of the procedure. To verify our code, we compare the Hilbert transform in Praat with a widely applied function for the same purpose in MATLAB (“hilbert(...)”). We can confirm that both methods arrive at identical outputs.

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Additional indexing

Item Type:Conference or Workshop Item (Speech), not refereed, original work
Communities & Collections:06 Faculty of Arts > Department of Comparative Linguistics
06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
490 Other languages
890 Other literatures
410 Linguistics
Language:English
Event End Date:12 September 2016
Deposited On:08 Nov 2016 13:11
Last Modified:29 May 2017 07:33
Publisher:ISCA
Publisher DOI:https://doi.org/10.21437/Interspeech.2016-1447

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