Voice or Content? — Exploring Impact of Speech Content on Age Estimation from Voice
Yuta Ide, Naohiro Tawara, Susumu Saito, Teppei Nakano, Tetsuji Ogawa · 2023
To investigate the impact of speech content on age estimation accuracy from voice data, we created a corpus of speech utterances featuring identical content spoken by individuals of varying ages. Subsequently, we analyzed the age estimation outcomes derived from this dataset. Previous studies have identified biases in age-labeled speech corpora regarding speaker age and vocabulary usage. Given that speech content typically varies with the speaker's age during conversations, it's plausible that age estimation results could be influenced by speech content. To address this concern, we developed a dataset in which speakers of different ages delivered speech content that was consistent across all speakers and tailored to the characteristics of each age group. We estimated the speakers' ages both manually, through crowdsourcing, and automatically and then conducted a significance test to assess whether speech content affected the age estimation results. Our findings indicated that neither the automatic age estimation system employed nor the manual age estimation outcomes were significantly impacted by speech content.