Open Speech and Language Resources

Phone: 425 247 4129
(Daniel Povey)

The AMI Corpus

Identifier: SLR16

Summary: Acoustic speech data and meta-data from The AMI corpus.

Category: Speech

License: THE CREATIVE COMMONS ATTRIBUTION-NONCOMMERCIAL-SHAREALIKE v2.0 LICENCE (modified, look for more details in the licence file and/or the AMI webpage)

ami_manual_1.6.1.tar.gz [21M]   (AMI annotation files (ver. 1.6.1) )
headset.tar.gz [24G]   ( Close-talking acosutic data )
Array1-01.tar.gz [7.4G]   ( Array1 distant acoustic data )
Array1-02.tar.gz [7.5G]   ( Array1 distant acoustic data )
Array1-03.tar.gz [7.6G]   ( Array1 distant acoustic data )
Array1-04.tar.gz [7.5G]   ( Array1 distant acoustic data )
Array1-05.tar.gz [7.5G]   ( Array1 distant acoustic data )
Array1-06.tar.gz [7.5G]   ( Array1 distant acoustic data )
Array1-07.tar.gz [7.5G]   ( Array1 distant acoustic data )
Array1-08.tar.gz [7.6G]   ( Array1 distant acoustic data )

About this resource:

This is a mirror of The AMI Corpus acoustic data originally hosted on

The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals synchronized to a common timeline. These include close-talking and far-field microphones, individual and room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings, the participants also have unsynchronized pens available to them that record what is written. The meetings were recorded in English using three different rooms with different acoustic properties, and include mostly non-native speakers.

The associated paper(s) describing the data:
  • Jean Carletta (2007). Unleashing the killer corpus: experiences in creating the multi-everything AMI Meeting Corpus. Language Resources and Evaluation Journal 41(2): 181-190. pdf
  • Steve Renals, Thomas Hain, and HervĂ© Bourlard (2007). Recognition and interpretation of meetings: The AMI and AMIDA projects. In Proc. IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU '07). pdf

External URL:   The official AMI corpus webpage