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International Journal of Speech Technology
Erschienen in: International Journal of Speech Technology 1/2022

06.09.2021

Automatic short utterance speaker recognition using stationary wavelet coefficients of pitch synchronised LP residual

verfasst von: V. R Sreehari, Leena Mary

Erschienen in: International Journal of Speech Technology | Ausgabe 1/2022

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Abstract

Automatic speaker recognition (ASR) is a challenging task when the duration of the test speech is very short i.e., a few seconds. Source features extracted from short speech utterances are shown to be effective for such cases. This paper proposes a system based on LP residual for text independent speaker recognition. Discrete wavelet transform (DWT) and stationary wavelet transform (SWT) are experimented to parameterize the LP residual. DWT works well in case of denoising and compression. SWT works well in reconstructing the noised signal at higher levels of decomposition than DWT. SWT/DWT coefficients of LP residual are used for implementing an i-vector/P-LDA based speaker recognition system. Effectiveness of the system is evaluated by using 10 s–10 s task of NIST speaker recognition evaluation (SRE) 2010 database. To evaluate robustness in degraded environments, the speech files are mixed with white noise from NOISEX-92 database. Speaker recognition using SWT level-3 results in an equal error rate (EER) of 40 and decision cost function (DCF) of 0.3956 for voice part of the signal in 10 s training—10 s testing data set. It has been shown that the proposed method gives robust speaker recognition performance in terms of DCF.
Vorheriger Artikel Exploiting variable length segments with coarticulation effect in online speech recognition based on deep bidirectional recurrent neural network and context-sensitive segment
Nächster Artikel Using novel method: Real Cepstral Discrete Cosine Transform, for detecting Parkinson from multiple system atrophy, other neurological diseases and healthy cases using voice analysis

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Metadaten
Titel
Automatic short utterance speaker recognition using stationary wavelet coefficients of pitch synchronised LP residual
verfasst von
V. R Sreehari
Leena Mary
Publikationsdatum
06.09.2021
Verlag
Springer US
Erschienen in
International Journal of Speech Technology / Ausgabe 1/2022
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-021-09895-z

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