A review of ASR technologies for children's speech

Automatically Recognising European Portuguese Children’s Speech

“…However, it is well known that automatically recognising children's speech is a very challenging task. Recognisers trained on adult speech tend to perform substantially worse when used by children [1][2][3][4][5][6]. Moreover, word error rates (WERs) on children's speech are usually much higher than those on adult speech, even when using a recogniser trained on children's speech, and they show a gradual decrease as the children get older [1][2][3][4][5][6][7].…”

“…The difficulty of automatically recognising children's speech can be attributed to it being acoustically and linguistically very different from adult speech [1,2]. For instance, due to their smaller vocal tracts, the fundamental and formant frequencies of children's speech are higher [1,2,[7][8][9]. What is particularly characteristic of children's speech is its higher variability as compared with adult speech, both within and across speakers [1,2].…”

“…For instance, due to their smaller vocal tracts, the fundamental and formant frequencies of children's speech are higher [1,2,[7][8][9]. What is particularly characteristic of children's speech is its higher variability as compared with adult speech, both within and across speakers [1,2]. This variability is caused by rapid developmental changes in their anatomy, speech production etc., and manifests itself, for example, in speech rate, in the degree of spontaneity, in the frequency of disfluencies, in the values of fundamental and formant frequencies, as well as in pronunciation quality [1,2,[7][8][9][10][11].…”

“…What is particularly characteristic of children's speech is its higher variability as compared with adult speech, both within and across speakers [1,2]. This variability is caused by rapid developmental changes in their anatomy, speech production etc., and manifests itself, for example, in speech rate, in the degree of spontaneity, in the frequency of disfluencies, in the values of fundamental and formant frequencies, as well as in pronunciation quality [1,2,[7][8][9][10][11]. The highly variable values of acoustic parameters converge to adult levels at around 13-15 years of age [9].…”

Improvement of a speech recognizer for standardized medical assessment of children's speech by integration of prior knowledge

“…This is achieved by different age-dependent acoustic models and by different test-dependent language models. The usage of age-dependent acoustic models is motivated by the fact, that the voice of children is changing during a short period of time [9].…”