Age recognition for spoken dialogue systems: do we need it?

Wolters, Maria; Vipperla, Ravichander; Renals, Steve

doi:10.21437/interspeech.2009-440

Cited by 6 publications

(1 citation statement)

References 18 publications

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“…These results are consistent with the findings in [13] where for an older test set, acoustic models trained on older voices resulted in about 3-5% absolute improvement in WER over acoustic models trained on younger adult speech. The mismatch in the acoustic space of younger and older people has also been exploited in speaker age group classification tasks [40,41].…”

Section: Phoneme Acoustic Likelihoods and Phoneme Recognition Ratesmentioning

confidence: 99%

Ageing Voices: The Effect of Changes in Voice Parameters on ASR Performance

Vipperla¹,

Renals²,

Frankel³

2010

EURASIP Journal on Audio, Speech, and Music Processing

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With ageing, human voices undergo several changes which are typically characterized by increased hoarseness and changes in articulation patterns. In this study, we have examined the effect on Automatic Speech Recognition (ASR) and found that the Word Error Rates (WER) on older voices is 10% absolute higher compared to those of adult voices. Subsequently, we compared several voice source parameters including fundamental frequency, jitter, shimmer, harmonicity, and cepstral peak prominence of adult and older males. Several of these parameters show statistically significant difference for the two groups. However, artificially increasing jitter and shimmer measures do not effect the ASR accuracies significantly. Artificially lowering the fundamental frequency degrades the ASR performance marginally but this drop in performance can be overcome to some extent using Vocal Tract Length Normalisation (VTLN). Overall, we observe that the changes in the voice source parameters do not have a significant impact on ASR performance. Comparison of the likelihood scores of all the phonemes for the two age groups show that there is a systematic mismatch in the acoustic space of the two age groups. Comparison of the phoneme recognition rates show that mid vowels, nasals, and phonemes that depend on the ability to create constrictions with tongue tip for articulation are more affected by ageing than other phonemes.

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Section: Phoneme Acoustic Likelihoods and Phoneme Recognition Ratesmentioning

confidence: 99%