A multimodal spectral approach to characterize rhythm in natural speech

Anna Alexandrou, Timo Saarinen, Jan Kujala, Riitta Salmelin

Research output: Contribution to journalArticleScientificpeer-review

15 Citations (Scopus)
196 Downloads (Pure)


Human utterances demonstrate temporal patterning, also referred to as rhythm. While simple oromotor behaviors (e.g., chewing) feature a salient periodical structure, conversational speech displays a time-varying quasi-rhythmic pattern. Quantification of periodicity in speech is challenging. Unimodal spectral approaches have highlighted rhythmic aspects of speech. However, speech is a complex multimodal phenomenon that arises from the interplay of articulatory, respiratory, and vocal systems. The present study addressed the question of whether a multimodal spectral approach, in the form of coherence analysis between electromyographic (EMG) and acoustic signals, would allow one to characterize rhythm in natural speech more efficiently than a unimodal analysis. The main experimental task consisted of speech production at three speaking rates; a simple oromotor task served as control. The EMG-acoustic coherence emerged as a sensitive means of tracking speech rhythm, whereas spectral analysis of either EMG or acoustic amplitude envelope alone was less informative. Coherence metrics seem to distinguish and highlight rhythmic structure in natural speech.

Original languageEnglish
Pages (from-to)215-226
Number of pages12
JournalJournal of the Acoustical Society of America
Issue number1
Publication statusPublished - 2016
MoE publication typeA1 Journal article-refereed


  • Coherence
  • Speech analysis


Dive into the research topics of 'A multimodal spectral approach to characterize rhythm in natural speech'. Together they form a unique fingerprint.

Cite this