D. Martínez, L. Burget, L. Ferrer and N. Scheffer, “iVector-based prosodic system for language identification,” 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012, pp. 4861-4864, doi: 10.1109/ICASSP.2012.6289008.
Abstract
Prosody is the part of speech where rhythm, stress, and intonation are reflected. In language identification tasks, these
characteristics are assumed to be language dependent, and
thus the language can be identified from them. In this paper, an automatic language recognition system that extracts
prosody information from speech and makes decisions about
the language with a generative classifier based on iVectors is
built. The system is tested on the NIST LRE09 dataset. The
results are still not comparable to state-of-the-art acoustic and
phonotactic systems. However, they are promising and the fusion of the new approach with an iVector-based acoustic system is found to bring further improvements over the latter.
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