peterf@2: Summary
peterf@2: -------------------
peterf@2: This software relates to results reported in Foster et al. (2015). Scripts are included for analysing annotator agreement and for obtaining baseline GMM results, using the CHiME-Home dataset. Finally, the scripts are provided for obtaining the annotations.
peterf@2: 
peterf@2: NB: The CHiME-Home dataset is not included. The dataset (recordings & annotations) is available at TODO.
peterf@2: 
peterf@2: The scripts were developed and tested on Linux environments, using Python 2.7.6. Portability to other environments is not expected.
peterf@2: 
peterf@2: Overview of directory structure and scripts
peterf@2: -------------------
peterf@2: annotation_scripts/
peterf@2:   Contains scripts used to obtain annotations
peterf@2:   annotationkit_create_annotation_protocol.py
peterf@2:     Prepares annotation protocol CSV from list of audio files
peterf@2:   annotationkit_create_annotation_protocol_wrapper.sh
peterf@2:     Wrapper shell script for annotationkit_create_annotation_protocol.py
peterf@2:   annotationkit_play_chunks.py
peterf@2:     Play back list of audio chunks, based on specified annotation protocol CSV and read annotation strings from terminal
peterf@2:   warmup_phase/
peterf@2:     Contains preliminary scripts used to create protocol files for annotator warm-up phases (cf. Foster et al., 2015)
peterf@2: 
peterf@2: analysis_of_annotations/evaluate_annotations.py
peterf@2:   Code relevant to analysis of CHiME-Home annotations (not audio)
peterf@2: 
peterf@2: gmm_baseline_experiments/
peterf@2:   Contains scripts for baseline GMM evaluation.
peterf@2:     run_experiments.py
peterf@2: 	  Main script for baseline GMM evaluation
peterf@2: 
peterf@2: How-to
peterf@2: -------------------
peterf@2: Reproduce analysis of annotations reported in Foster et al. (2015) :-
peterf@2: 
peterf@2:   1) Modify evaluate_annotations.py, so that variable DatasetPath points to directory containing CHiME-Home dataset
peterf@2:   2) Execute evaluate_annotations.py
peterf@2:   The script writes textual analysis data to standard output; a figure pdf is written to analysis_of_annotations/figures subdirectory.
peterf@2: 
peterf@2: Reproduce baseline results reported in Foster et al. (2015) :-
peterf@2: 
peterf@2:   1) Modify run_experiments.py, so that Settings['paths']['chime_home']['basepath'] points to Directory containing CHiME-Home dataset; Settings['paths']['resultsdir'] and Settings['paths']['featuresdir'] should respectively point to desired directories for storing pickle files of data structures containing results and features
peterf@2:   2) Execute run_experiments.py
peterf@2:   The script writes a figure pdf to gmm_baseline_experiments/figures subdirectory.
peterf@2: 
peterf@2: Adapt annotation scripts for alternative purposes :-
peterf@2: 
peterf@2:   1) Modify annotationkit_create_annotation_protocol.py. The purpose of this script is to read a list of audio files from standard input and write CSV to standard output; as presently implemented, each input file is a audio segment from which a set of 4-second chunks are sampled (as defined in script header, and sampling without replacement). The list of chunks is written to an output CSV, and defines a `protocol' file for use with the annotation script annotationkit_play_chunks.py. Variables chunkDuration and sampleRate should match desired chunk duration and given audio sample rate.
peterf@2:   2) Modify annotationkit_play_chunks_wrapper.sh so that parameters chunkDuration, sampleRate are consistent with annotationkit_create_annotation_protocol.py. Further, modify parameters PermittedAnnotationCharacters, LoneAnnotationCharacters, LabelMap to reflect chosen label alphabet. NB: As implemented, using the protocol CSV, annotationkit_play_chunks.py seeks within each audio segment to locate each audio chunk, thus no explicit segmentation of input audio is required.
peterf@2: 
peterf@2: 
peterf@2: 
peterf@2: How to cite
peterf@2: -------------------
peterf@2: P. Foster, S. Sigtia, S. Krstulovic, J. Barker, M. D. Plumbley. "CHiME-Home: A Dataset for Sound Source Recognition in a Domestic Environment," in Proceedings of the 11th Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2015.