Emotion, age, and gender classification in children's speech by humans and machines
Yükleniyor...
Dosyalar
Tarih
2017
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Academic Press Ltd- Elsevier Science Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this article, we present the first child emotional speech corpus in Russian, called EmoChildRu, collected from 3 to 7 years old children. The base corpus includes over 20 K recordings (approx. 30 h), collected from 120 children. Audio recordings are carried out in three controlled settings by creating different emotional states for children: playing with a standard set of toys; repetition of words from a toy-parrot in a game store setting; watching a cartoon and retelling of the story, respectively. This corpus is designed to study the reflection of the emotional state in the characteristics of voice and speech and for studies of the formation of emotional states in ontogenesis. A portion of the corpus is annotated for three emotional states (comfort, discomfort, neutral). Additional data include the results of the adult listeners' analysis of child speech, questionnaires, as well as annotation for gender and age in months. We also provide several baselines, comparing human and machine estimation on this corpus for prediction of age, gender and comfort state. While in age estimation, the acoustics-based automatic systems show higher performance, they do not reach human perception levels in comfort state and gender classification. The comparative results indicate the importance and necessity of developing further linguistic models for discrimination. (C) 2017 Elsevier Ltd. All rights reserved.
Açıklama
Anahtar Kelimeler
Emotional child speech, Perception experiments, Spectrographic analysis, Emotional states, Age recognition, Gender recognition, Computational paralinguistics, Recognition
Kaynak
Computer Speech and Language
WoS Q Değeri
Q2
Scopus Q Değeri
Q2
Cilt
46