In the first two years of life, infants make astounding strides in language acquisition. The following databases that tabulate empirical research on key language acquisition phenomena happening during that time frame:

• InVarInf Community-augmented meta-analysis on individual variation between performance in infant speech perception tasks and some other factor 
• InPhonDB Community-augmented meta-analysis on infant speech sound discrimination (visualize the contents of this database) 
• Scope expanded! Now contains vowels and consonants
• InWordDB Community-augmented meta-analysis on infants' recognition of words (and wordforms) 
• Scope expanded! Now contains: Segmentation of natural native speech; natural nonnative speech; content versus function words
• Null results from unpublished work contributed 
• StatLearnDB Community-augmented meta-analysis on infants' statistical segmentation of artificial mini-languages

All databases are open to contributions, be it by adding data or expanding their scope.

Please also refer to Metalab, for more CAMAs and for detailed instructions on contributing to the effort.

The following databases are also of potential interest:

• DBIfNIRS Table with all infant fNIRS studies (language or otherwise) published before 2011 (and some thereafter) 
• Report on infant-directed speech Tables on the acoustic characteristics of infant-, compared to adult-, directed speech and their effects on infant perception and development 

How to create your own community-augmented meta-analysis (CAMA)

Are you interested in creating your own database? Visit our tutorial page for basic instructions.

Further information on CAMAs

Publications:

The paper introducing CAMAs: