annotations.TGA package

Submodules

annotations.TGA.sppastga module

filename

sppas.src.annotations.TGA.sppastga.py

author

Brigitte Bigi

contact

develop@sppas.org

summary

SPPAS integration of TGA automatic annotation

class annotations.TGA.sppastga.sppasTGA(log=None)[source]

Bases: annotations.baseannot.sppasBaseAnnotation

Estimate TGA on a tier – from D. Gibbon.

Create time groups then map them into a dictionary where:

  • key is a label assigned to the time group;

  • value is the list of observed durations of segments in this TG.

__init__(log=None)[source]

Create a new sppasTGA instance.

Log is used for a better communication of the annotation process and its results. If None, logs are redirected to the default logging system.

Parameters

log – (sppasLog) Human-readable logs.

convert(syllables)[source]

Estimate TGA on the given syllables.

Parameters

syllables – (sppasTier)

Returns

(sppasTranscription)

fix_options(options)[source]

Fix all options.

Available options are:

  • with_radius

  • original

  • annotationpro

  • tg_prefix_label

Parameters

options – (sppasOption)

get_input_patterns()[source]

Pattern this annotation expects for its input filename.

get_inputs(input_files)[source]

Return the the tier with aligned tokens.

Parameters

input_files – (list)

Raise

NoTierInputError

Returns

(sppasTier)

get_output_pattern()[source]

Pattern this annotation uses in an output filename.

run(input_files, output=None)[source]

Run the automatic annotation process on an input.

Parameters

  • input_files – (list of str) Syllabification

  • output – (str) the output file name

Returns

(sppasTranscription)

set_intercept_slope_annotationpro(value)[source]

Estimate intercepts and slopes with the method of annotationpro.

Default is True.

Parameters

value – (boolean)

set_intercept_slope_original(value)[source]

Estimate intercepts and slopes with the original method.

Default is False.

Parameters

value – (boolean)

set_tg_prefix_label(prefix)[source]

Fix the prefix to add to each TG.

Parameters

prefix – (str) Default is ‘tg_’

set_with_radius(with_radius)[source]

Set the with_radius option, used to estimate the duration.

Parameters

with_radius – (int)

  • 0 means to use Midpoint;

  • negative value means to use R-;

  • positive radius means to use R+.

syllables_to_timegroups(syllables)[source]

Create the time group intervals.

Parameters

syllables – (sppasTier)

Returns

(sppasTier) Time groups

syllables_to_timesegments(syllables)[source]

Create the time segments intervals.

Time segments are time groups with serialized syllables.

Parameters

syllables –

Returns

(sppasTier) Time segments

static tga_to_tier(tga_result, timegroups, tier_name, tag_type='float')[source]

Create a tier from one of the TGA result.

Parameters

  • tga_result – One of the results of TGA

  • timegroups – (sppasTier) Time groups

  • tier_name – (str) Name of the output tier

  • tag_type – (str) Type of the sppasTag to be included

Returns

(sppasTier)

static tga_to_tier_reglin(tga_result, timegroups, intercept=True)[source]

Create tiers of intercept,slope from one of the TGA result.

Parameters

  • tga_result – One of the results of TGA

  • timegroups – (sppasTier) Time groups

  • intercept – (boolean) Export the intercept.

If False, export Slope.

Returns

(sppasTier)

timegroups_to_durations(syllables, timegroups)[source]

Return a dict with timegroups and the syllable durations.

Parameters

  • syllables – (sppasTier) Syllables

  • timegroups – (sppasTier) Time groups

Returns

(dict)

annotations.TGA.timegroupanalysis module

filename

sppas.src.annotations.TGA.timegroupanalysis.py

author

Brigitte Bigi

contact

develop@sppas.org

summary

The time group analyzer partly re-implemented

class annotations.TGA.timegroupanalysis.TimeGroupAnalysis(dict_items)[source]

Bases: sppas.src.calculus.stats.descriptivesstats.sppasDescriptiveStatistics

Time Group Analyzer estimator class.

TGA: Time Group Analyzer is an online tool for speech annotation mining written by Dafydd Gibbon (Universität Bielefeld).

See: <http://wwwhomes.uni-bielefeld.de/gibbon/TGA/>

This class estimates TGA on a set of data values, stored in a dictionary:

  • key is the name of the time group;

  • value is the list of durations of each segments in the time group.

>>> d = {'tg1':[1.0, 1.2, 3.2, 4.1] , 'tg2':[2.9, 3.3, 3.6, 5.8]}
>>> tga = TimeGroupAnalysis(d)
>>> total = tga.total()
>>> intercept, slope = tga.intercept_slope()
>>> print(slope['tg_1'])
>>> print(slope['tg_2'])
__init__(dict_items)[source]

TGA - The Time Group Analyzer.

Parameters

dict_items – (dict) a dict of a list of durations.

intercept_slope()[source]

Estimate the intercept like AnnotationPro of data values.

Create the list of points (x,y) of each TG where:

  • x is the timestamps

  • y is the duration

Returns

(dict) a dict of (key, (intercept, slope)) of float values

intercept_slope_original()[source]

Estimate the intercept like the original TGA of data values.

Create the list of points (x,y) of each TG where:

  • x is the position

  • y is the duration

Returns

(dict) a dict of (key, (intercept,slope)) of float values

nPVI()[source]

Estimate the Normalized Pairwise Variability Index of data values.

Returns

(dict) a dictionary of (key, nPVI) of float values

rPVI()[source]

Estimate the Raw Pairwise Variability Index of data values.

Returns

(dict) a dictionary of (key, nPVI) of float values

Module contents

filename

sppas.src.annotations.TGA.__init__.py

author

Brigitte Bigi

contact

develop@sppas.org

summary

Time-Group Analyzer automatic annotation.

TGA: Time Group Analyzer is an online tool for speech annotation mining written by Dafydd Gibbon, emeritus professor of English and General Linguistics at Bielefeld University..

TGA software calculates, inter alia, mean, median, rPVI, nPVI, slope and intercept functions within inter-pausal groups.

For details, read the following reference:
Dafydd Gibbon (2013).
TGA: a web tool for Time Group Analysis.
Tools ans Resources for the Analysis of Speech Prosody,
Aix-en-Provence, France, pp. 66-69.

See also: <http://wwwhomes.uni-bielefeld.de/gibbon/TGA/>

class annotations.TGA.TimeGroupAnalysis(dict_items)[source]

Bases: sppas.src.calculus.stats.descriptivesstats.sppasDescriptiveStatistics

Time Group Analyzer estimator class.

TGA: Time Group Analyzer is an online tool for speech annotation mining written by Dafydd Gibbon (Universität Bielefeld).

See: <http://wwwhomes.uni-bielefeld.de/gibbon/TGA/>

This class estimates TGA on a set of data values, stored in a dictionary:

  • key is the name of the time group;

  • value is the list of durations of each segments in the time group.

>>> d = {'tg1':[1.0, 1.2, 3.2, 4.1] , 'tg2':[2.9, 3.3, 3.6, 5.8]}
>>> tga = TimeGroupAnalysis(d)
>>> total = tga.total()
>>> intercept, slope = tga.intercept_slope()
>>> print(slope['tg_1'])
>>> print(slope['tg_2'])
__init__(dict_items)[source]

TGA - The Time Group Analyzer.

Parameters

dict_items – (dict) a dict of a list of durations.

intercept_slope()[source]

Estimate the intercept like AnnotationPro of data values.

Create the list of points (x,y) of each TG where:

  • x is the timestamps

  • y is the duration

Returns

(dict) a dict of (key, (intercept, slope)) of float values

intercept_slope_original()[source]

Estimate the intercept like the original TGA of data values.

Create the list of points (x,y) of each TG where:

  • x is the position

  • y is the duration

Returns

(dict) a dict of (key, (intercept,slope)) of float values

nPVI()[source]

Estimate the Normalized Pairwise Variability Index of data values.

Returns

(dict) a dictionary of (key, nPVI) of float values

rPVI()[source]

Estimate the Raw Pairwise Variability Index of data values.

Returns

(dict) a dictionary of (key, nPVI) of float values

class annotations.TGA.sppasTGA(log=None)[source]

Bases: annotations.baseannot.sppasBaseAnnotation

Estimate TGA on a tier – from D. Gibbon.

Create time groups then map them into a dictionary where:

  • key is a label assigned to the time group;

  • value is the list of observed durations of segments in this TG.

__init__(log=None)[source]

Create a new sppasTGA instance.

Log is used for a better communication of the annotation process and its results. If None, logs are redirected to the default logging system.

Parameters

log – (sppasLog) Human-readable logs.

convert(syllables)[source]

Estimate TGA on the given syllables.

Parameters

syllables – (sppasTier)

Returns

(sppasTranscription)

fix_options(options)[source]

Fix all options.

Available options are:

  • with_radius

  • original

  • annotationpro

  • tg_prefix_label

Parameters

options – (sppasOption)

get_input_patterns()[source]

Pattern this annotation expects for its input filename.

get_inputs(input_files)[source]

Return the the tier with aligned tokens.

Parameters

input_files – (list)

Raise

NoTierInputError

Returns

(sppasTier)

get_output_pattern()[source]

Pattern this annotation uses in an output filename.

run(input_files, output=None)[source]

Run the automatic annotation process on an input.

Parameters

  • input_files – (list of str) Syllabification

  • output – (str) the output file name

Returns

(sppasTranscription)

set_intercept_slope_annotationpro(value)[source]

Estimate intercepts and slopes with the method of annotationpro.

Default is True.

Parameters

value – (boolean)

set_intercept_slope_original(value)[source]

Estimate intercepts and slopes with the original method.

Default is False.

Parameters

value – (boolean)

set_tg_prefix_label(prefix)[source]

Fix the prefix to add to each TG.

Parameters

prefix – (str) Default is ‘tg_’

set_with_radius(with_radius)[source]

Set the with_radius option, used to estimate the duration.

Parameters

with_radius – (int)

  • 0 means to use Midpoint;

  • negative value means to use R-;

  • positive radius means to use R+.

syllables_to_timegroups(syllables)[source]

Create the time group intervals.

Parameters

syllables – (sppasTier)

Returns

(sppasTier) Time groups

syllables_to_timesegments(syllables)[source]

Create the time segments intervals.

Time segments are time groups with serialized syllables.

Parameters

syllables –

Returns

(sppasTier) Time segments

static tga_to_tier(tga_result, timegroups, tier_name, tag_type='float')[source]

Create a tier from one of the TGA result.

Parameters

  • tga_result – One of the results of TGA

  • timegroups – (sppasTier) Time groups

  • tier_name – (str) Name of the output tier

  • tag_type – (str) Type of the sppasTag to be included

Returns

(sppasTier)

static tga_to_tier_reglin(tga_result, timegroups, intercept=True)[source]

Create tiers of intercept,slope from one of the TGA result.

Parameters

  • tga_result – One of the results of TGA

  • timegroups – (sppasTier) Time groups

  • intercept – (boolean) Export the intercept.

If False, export Slope.

Returns

(sppasTier)

timegroups_to_durations(syllables, timegroups)[source]

Return a dict with timegroups and the syllable durations.

Parameters

  • syllables – (sppasTier) Syllables

  • timegroups – (sppasTier) Time groups

Returns

(dict)