Acoustics API¶

Classes¶

class polyglotdb.acoustics.classes.Track[source]¶

Track class to contain, select, and manage TimePoint objects

Attributes:	points : iterable of `TimePoint` Time points with values of the acoustic track

add(point)[source]¶

Add a TimePoint to the track

Parameters:	point : `TimePoint` Time point to add

items()[source]¶

Generator for returning tuples of the time point and values

Returns:	generator Tuples of time points and values

keys()[source]¶

Get a list of all keys for TimePoints that the Track has

Returns:	list All keys on TimePoint objects

slice(begin, end)[source]¶

Create a slice of the acoustic track between two times

Parameters:	begin : float Begin time for the slice end : float End time for the slice
Returns:	`Track` Track constructed from just the time points in the specified time

times()[source]¶

Get a list of all time points in the track

Returns:	list Sorted time points

class polyglotdb.acoustics.classes.TimePoint(time)[source]¶

Class for handling acoustic measurements at a specific time point

Attributes:	time : float The time of the time point values : dict Dictionary of acoustic measures for the given time point

add_value(name, value)[source]¶

Add a new named measure and value to the TimePoint

Parameters:	name : str Name of the measure value : object Measure value

has_value(name)[source]¶

Check whether a time point contains a named measure

Parameters:	name : str Name of the measure
Returns:	bool True if name is in values and has a value

select_values(columns)[source]¶

Generate a dictionary of only the specified measurement names

Parameters:	columns : iterable Iterable of measurement names to include
Returns:	dict Subset of values if their name is in the specified columns

update(point)[source]¶

Update values in this time point from another TimePoint

Parameters:	point : `polyglotdb.acoustics.classes.TimePoint` TimePoint to get values from

Segments¶

polyglotdb.acoustics.segments.generate_segments(corpus_context, annotation_type='utterance', subset=None, file_type='vowel', duration_threshold=0.001, padding=0, fetch_subannotations=False)[source]¶

Generate segment vectors for an annotation type, to be used as input to analyze_file_segments.

Parameters:

corpus_context : CorpusContext: The CorpusContext object of the corpus
annotation_type : str, optional: The type of annotation to use in generating segments, defaults to utterance
subset : str, optional: Specify a subset to use for generating segments
file_type : str, optional: One of ‘low_freq’, ‘vowel’, or ‘consonant’, specifies the type of audio file to use
duration_threshold: float, optional: Segments with length shorter than this value (in seconds) will not be included

Returns:

SegmentMapping: Object containing segments to be analyzed

polyglotdb.acoustics.segments.generate_vowel_segments(corpus_context, duration_threshold=None, padding=0, vowel_label='vowel')[source]¶

Generate segment vectors for each vowel, to be used as input to analyze_file_segments.

Parameters:	corpus_context : `polyglot.corpus.context.CorpusContext` The CorpusContext object of the corpus duration_threshold: float, optional Segments with length shorter than this value (in seconds) will not be included
Returns:	SegmentMapping Object containing vowel segments to be analyzed

polyglotdb.acoustics.segments.generate_utterance_segments(corpus_context, file_type='vowel', duration_threshold=None, padding=0)[source]¶

Generate segment vectors for each utterance, to be used as input to analyze_file_segments.

Parameters:	corpus_context : `polyglot.corpus.context.CorpusContext` The CorpusContext object of the corpus file_type : str, optional One of ‘low_freq’, ‘vowel’, or ‘consonant’, specifies the type of audio file to use duration_threshold: float, optional Segments with length shorter than this value (in seconds) will not be included
Returns:	SegmentMapping Object containing utterance segments to be analyzed

Formants¶

polyglotdb.acoustics.formants.base.analyze_formant_tracks(corpus_context, vowel_label=None, source='praat', call_back=None, stop_check=None, multiprocessing=True)[source]¶

Analyze formants of an entire utterance, and save the resulting formant tracks into the database.

Parameters:	corpus_context : CorpusContext corpus context to use vowel_label : str, optional Optional subset of phones to compute tracks over. If None, then tracks over utterances are computed. call_back : callable call back function, optional stop_check : callable stop check function, optional

polyglotdb.acoustics.formants.base.analyze_formant_points(corpus_context, call_back=None, stop_check=None, vowel_label='vowel', duration_threshold=None, multiprocessing=True)[source]¶

First pass of the algorithm; generates prototypes.

Parameters:	corpus_context : `polyglot.corpus.context.CorpusContext` The CorpusContext object of the corpus. call_back : callable Information about callback. stop_check : string Information about stop check. vowel_label : str The subset of phones to analyze. duration_threshold : float, optional Segments with length shorter than this value (in milliseconds) will not be analyzed.
Returns:	dict Track data

polyglotdb.acoustics.formants.refined.analyze_formant_points_refinement(corpus_context, vowel_label='vowel', duration_threshold=0, num_iterations=1, call_back=None, stop_check=None, vowel_prototypes_path='', drop_formant=False, multiprocessing=True, output_tracks=False)[source]¶

Extracts F1, F2, F3 and B1, B2, B3.

Parameters:

corpus_context : CorpusContext: The CorpusContext object of the corpus.
vowel_label : str: The subset of phones to analyze.
duration_threshold : float, optional: Segments with length shorter than this value (in milliseconds) will not be analyzed.
num_iterations : int, optional: How many times the algorithm should iterate before returning values.
output_tracks : bool, optional: Whether to save only the formant values as a point at 0.33 if false or have a track over the entire vowel duration if true.

Returns:

prototype_metadata : dict: Means of F1, F2, F3, B1, B2, B3 and covariance matrices per vowel class.

Conch function generators¶

polyglotdb.acoustics.formants.helper.generate_base_formants_function(corpus_context, gender=None, source='praat')[source]¶

Parameters:

corpus_context : polyglot.corpus.context.CorpusContext: The CorpusContext object of the corpus.
gender : str: The gender to use for the function, if “M”(male) then the max frequency is 5000 Hz, otherwise 5500
source : str: The source of the function, if it is “praat” then the formants will be calculated with Praat over each segment otherwise it will simply be tracks
Returns
——-
formant_function : Partial function object: The function used to call Praat.

polyglotdb.acoustics.formants.helper.generate_formants_point_function(corpus_context, gender=None)[source]¶

Generates a function used to call Praat to measure formants and bandwidths with variable num_formants.

Parameters:	corpus_context : `CorpusContext` The CorpusContext object of the corpus. min_formants : int The minimum number of formants to measure with on subsequent passes (default is 4). max_formants : int The maximum number of formants to measure with on subsequent passes (default is 7).
Returns:	formant_function : Partial function object The function used to call Praat.

polyglotdb.acoustics.formants.helper.generate_variable_formants_point_function(corpus_context, min_formants, max_formants)[source]¶

Generates a function used to call Praat to measure formants and bandwidths with variable num_formants. This specific function returns a single point per formant at a third of the way through the segment

Parameters:	corpus_context : `CorpusContext` The CorpusContext object of the corpus. min_formants : int The minimum number of formants to measure with on subsequent passes (default is 4). max_formants : int The maximum number of formants to measure with on subsequent passes (default is 7).
Returns:	formant_function : Partial function object The function used to call Praat.

Intensity¶

polyglotdb.acoustics.intensity.analyze_intensity(corpus_context, source='praat', call_back=None, stop_check=None, multiprocessing=True)[source]¶

Analyze intensity of an entire utterance, and save the resulting intensity tracks into the database.

Parameters:	corpus_context : `CorpusContext` corpus context to use source : str Source program to use (only praat available) call_back : callable call back function, optional stop_check : function stop check function, optional multiprocessing : bool Flag to use multiprocessing rather than threading

Conch function generators¶

polyglotdb.acoustics.intensity.generate_base_intensity_function(corpus_context)[source]¶

Generate an Intensity function from Conch

Parameters:	corpus_context : `CorpusContext` CorpusContext to use for getting path to Praat (if not on the system path)
Returns:	`PraatSegmentIntensityTrackFunction` Intensity analysis function

Pitch¶

polyglotdb.acoustics.pitch.base.analyze_pitch(corpus_context, source='praat', algorithm='base', call_back=None, absolute_min_pitch=50, absolute_max_pitch=500, adjusted_octaves=1, stop_check=None, multiprocessing=True)[source]¶

Parameters:

corpus_context : AudioContext
source : str: Program to use for analyzing pitch, either praat or reaper
algorithm : str: Algorithm to use, base, gendered, or speaker_adjusted
absolute_min_pitch : int: Absolute pitch floor
absolute_max_pitch : int: Absolute pitch ceiling
adjusted_octaves : int: How many octaves around the speaker’s mean pitch to set the speaker adjusted pitch floor and ceiling
stop_check : callable: Function to check whether processing should stop early
call_back : callable: Function to report progress
multiprocessing : bool: Flag whether to use multiprocessing or threading

Conch function generators¶

polyglotdb.acoustics.pitch.helper.generate_pitch_function(algorithm, min_pitch, max_pitch, path=None, kwargs=None)[source]¶

VOT¶

polyglotdb.acoustics.vot.base.analyze_vot(corpus_context, classifier, stop_label='stops', vot_min=5, vot_max=100, window_min=-30, window_max=30, overwrite_edited=False, call_back=None, stop_check=None, multiprocessing=False)[source]¶

Analyze VOT for stops using a pretrained AutoVOT classifier.

Parameters:

corpus_context : AudioContext
classifier : str: Path to an AutoVOT classifier model
stop_label : str: Label of subset to analyze
vot_min : int: Minimum VOT in ms
vot_max : int: Maximum VOT in ms
window_min : int: Window minimum in ms
window_max : int: Window maximum in Ms
overwrite_edited:: Whether to updated VOTs which have the property, edited set to True
call_back : callable: call back function, optional
stop_check : callable: stop check function, optional
multiprocessing : bool: Flag to use multiprocessing, otherwise will use threading

Other¶

polyglotdb.acoustics.other.analyze_track_script(corpus_context, acoustic_name, properties, script_path, duration_threshold=0.01, phone_class=None, arguments=None, call_back=None, file_type='consonant', stop_check=None, multiprocessing=True)[source]¶

polyglotdb.acoustics.other.analyze_script(corpus_context, phone_class=None, subset=None, annotation_type=None, script_path=None, duration_threshold=0.01, arguments=None, call_back=None, file_type='consonant', stop_check=None, multiprocessing=True)[source]¶

Perform acoustic analysis of phones using an input praat script.

Saves the measurement results from the praat script into the database under the same names as the Praat output columns Praat script requirements:

the only input is the full path to the sound file containing (only) the phone
the script prints the output to the Praat Info window in two rows (i.e. two lines).
the first row is a space-separated list of measurement names: these are the names that will be saved into the database
the second row is a space-separated list of the value for each measurement

Parameters:

corpus_context : CorpusContext: corpus context to use
phone_class : str: DEPRECATED, the name of an already encoded subset of phones on which the analysis will be run
subset : str, optional: the name of an already encoded subset of an annotation type, on which the analysis will be run
annotation_type : str: the type of annotation that the analysis will go over
script_path : str: full path to the praat script
duration_threshold : float: Minimum duration of segments to be analyzed
file_type : str: File type to use for the script (consonant = 16kHz sample rate, vowel = 11kHz, low_freq = 1200 Hz)
arguments : list: a list containing any arguments to the praat script (currently not working)
call_back : callable: call back function, optional
stop_check : callable: stop check function, optional
multiprocessing : bool: Flag to use multiprocessing, otherwise will use threading

Conch function generators¶

polyglotdb.acoustics.other.generate_praat_script_function(praat_path, script_path, arguments=None)[source]¶

Generate a partial function that calls the praat script specified. (used as input to analyze_file_segments)

Parameters:	praat_path : string full path to praat/praatcon script_path: string full path to the script arguments : list a list containing any arguments to the praat script, optional (currently not implemented)
Returns:	function the partial function which applies the Praat script to a phone and returns the script output