Vocal learning is a rare and complex behavioral trait that serves as a basis for the acquisition of human spoken language.
This type of vocal learning for which neural and molecular substrates have been well documented [3] is similar to human spoken language learning [7].
Notwithstanding, theories concerning the origin of human language and the neural substrates that support this capacity have proposed that (in some form or another), human spoken language is fundamentally different from other animal vocal communication systems.
For example, previous research indicated that video-counseling - in which a real human speaks and asks questions - can be a promising technique for health interventions [ 109].
Its involvement in human spoken language may be built on evolutionarily ancient circuits implicated in sensory motor functions and motor-skill learning (Fisher & Marcus 2006).
Such combinations (versus 'syntactic' concatenation of syllables and words) are a core feature of the phonological component of human spoken language [ 33].
Although the intent of the present study was to verify the presumed auditory nature of consonant replacement strategies in speech audiometric testing, the results of the analysis also address several aspects of human spoken word recognition models.
Humans speak: computers don't.
But the humans speak about him when they see me.
