252 lines
8.3 KiB
Python
252 lines
8.3 KiB
Python
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#!/usr/bin/env python3
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"""Functions for converting IPA symbols to and from feature vectors."""
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import dataclasses
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import typing
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from gruut_ipa.constants import (
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CONSONANTS,
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FEATURE_COLUMNS,
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FEATURE_EMPTY,
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FEATURE_KEYS,
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FEATURE_ORDINAL_COLUMNS,
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IPA,
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SCHWAS,
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VOWELS,
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Break,
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BreakType,
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Consonant,
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ConsonantPlace,
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ConsonantType,
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PhonemeLength,
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Schwa,
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Stress,
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Vowel,
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VowelHeight,
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VowelPlacement,
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)
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def to_vector(
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symbol: typing.Union[Vowel, Consonant, Schwa, Break]
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) -> typing.Sequence[float]:
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"""Converts a symbol into a feature vector"""
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features: typing.Dict[str, str] = {}
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if isinstance(symbol, Vowel):
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features["symbol_type"] = "phoneme"
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features["phoneme_type"] = "vowel"
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features["vowel_height"] = symbol.height.value
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features["vowel_place"] = symbol.placement.value
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features["vowel_rounded"] = "rounded" if symbol.rounded else "unrounded"
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features["phoneme_length"] = symbol.length.value
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if symbol.nasalated:
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features["diacritic"] = "nasalated"
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if symbol.stress is not None:
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features["vowel_stress"] = symbol.stress.value
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elif isinstance(symbol, Consonant):
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features["symbol_type"] = "phoneme"
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features["phoneme_type"] = "consonant"
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features["consonant_voiced"] = "voiced" if symbol.voiced else "unvoiced"
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features["consonant_type"] = symbol.type.value
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features["consonant_place"] = symbol.place.value
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features["consonant_sounds_like"] = symbol.sounds_like.value
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features["phoneme_length"] = symbol.length.value
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if symbol.velarized:
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features["diacritic"] = "velarized"
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elif isinstance(symbol, Schwa):
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features["symbol_type"] = "phoneme"
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features["phoneme_type"] = "schwa"
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features["phoneme_length"] = symbol.length.value
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if symbol.r_coloured:
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features["consonant_sounds_like"] = "r"
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elif isinstance(symbol, Break):
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features["symbol_type"] = "break"
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features["break_type"] = symbol.type.value
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else:
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# Unsupported symbol type
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raise ValueError(symbol)
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return features_to_vector(features)
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def from_vector(
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vector: typing.Sequence[float],
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) -> typing.Union[Vowel, Consonant, Schwa, Break]:
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"""Converts a feature vector back into a symbol"""
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features = vector_to_features(vector)
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if features["symbol_type"] == "break":
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break_type = BreakType(features["break_type"])
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return Break(break_type)
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if features["symbol_type"] == "phoneme":
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if features["phoneme_type"] == "vowel":
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height = VowelHeight(features["vowel_height"])
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placement = VowelPlacement(features["vowel_place"])
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rounded = features["vowel_rounded"] == "rounded"
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nasalated = features["diacritic"] == "nasalated"
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length = PhonemeLength(features["phoneme_length"])
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stress: typing.Optional[Stress] = None
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stress_val = features["vowel_stress"]
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if stress_val != FEATURE_EMPTY:
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stress = Stress(stress_val)
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for vowel in VOWELS.values():
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if (
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(vowel.height == height)
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and (vowel.placement == placement)
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and (vowel.rounded == rounded)
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and (vowel.nasalated == nasalated)
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):
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if (stress is None) and (length == PhonemeLength.NORMAL):
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# Don't need to make a copy
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return vowel
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return dataclasses.replace(vowel, stress=stress)
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raise ValueError(f"Unknown vowel: {features}")
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if features["phoneme_type"] == "consonant":
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c_type = ConsonantType(features["consonant_type"])
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place = ConsonantPlace(features["consonant_place"])
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voiced = features["consonant_voiced"] == "voiced"
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velarized = features["diacritic"] == "velarized"
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length = PhonemeLength(features["phoneme_length"])
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for consonant in CONSONANTS.values():
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if (
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(consonant.type == c_type)
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and (consonant.place == place)
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and (consonant.voiced == voiced)
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and (consonant.velarized == velarized)
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):
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if length == PhonemeLength.NORMAL:
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# Don't need to make a copy
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return consonant
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return dataclasses.replace(consonant, length=length)
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raise ValueError(f"Unknown vowel: {features}")
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if features["phoneme_type"] == "schwa":
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r_coloured = features["consonant_sounds_like"] == "r"
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length = PhonemeLength(features["phoneme_length"])
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for schwa in SCHWAS.values():
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if schwa.r_coloured == r_coloured:
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if length == PhonemeLength.NORMAL:
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# Don't need to make a copy
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return schwa
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return dataclasses.replace(schwa, length=length)
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raise ValueError(f"Unknown vowel: {features}")
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# Unsupported phoneme type
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raise ValueError(f"Unknown phoneme type: {features}")
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# Unsupported symbol type
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raise ValueError(f"Unknown symbol type: {features}")
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def string_to_symbol(symbol_str: str) -> typing.Union[Vowel, Consonant, Schwa, Break]:
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"""Get gruut IPA object for IPA symbol"""
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if not symbol_str:
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raise ValueError("Empty symbol")
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# Check break first
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if symbol_str == IPA.BREAK_WORD:
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return Break(BreakType.WORD)
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if symbol_str == IPA.BREAK_MINOR:
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return Break(BreakType.MINOR)
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if symbol_str == IPA.BREAK_MAJOR:
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return Break(BreakType.MAJOR)
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# Strip stress
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maybe_stress: typing.Optional[Stress] = None
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if symbol_str[0] == IPA.STRESS_PRIMARY:
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maybe_stress = Stress.PRIMARY
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symbol_str = symbol_str[1:]
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elif symbol_str[0] == IPA.STRESS_SECONDARY:
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maybe_stress = Stress.SECONDARY
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symbol_str = symbol_str[1:]
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if not symbol_str:
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raise ValueError("No letters")
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# Strip length
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length = PhonemeLength.NORMAL
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if symbol_str[-1] == IPA.HALF_LONG:
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length = PhonemeLength.SHORT
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symbol_str = symbol_str[:-1]
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elif symbol_str[-1] == IPA.LONG:
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length = PhonemeLength.LONG
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symbol_str = symbol_str[:-1]
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if not symbol_str:
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raise ValueError("No letters")
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# Look up
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maybe_vowel = VOWELS.get(symbol_str)
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if maybe_vowel is not None:
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return dataclasses.replace(maybe_vowel, stress=maybe_stress, length=length)
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maybe_consonant = CONSONANTS.get(symbol_str)
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if maybe_consonant is not None:
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return dataclasses.replace(maybe_consonant, length=length)
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maybe_schwa = SCHWAS.get(symbol_str)
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if maybe_schwa is not None:
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return dataclasses.replace(maybe_schwa, length=length)
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raise ValueError(f"Unsupported symbol type: {symbol_str}")
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def features_to_vector(features: typing.Mapping[str, str]) -> typing.Sequence[float]:
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"""Create phoneme feature vector from mapping"""
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vector: typing.List[float] = []
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for col, values in FEATURE_COLUMNS.items():
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value = features.get(col, FEATURE_EMPTY)
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if col in FEATURE_ORDINAL_COLUMNS:
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# Single value normalized by number of possible values
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vector.append(values.index(value) / len(values))
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else:
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# One-hot vector
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for v in values:
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vector.append(1.0 if (v == value) else 0.0)
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return vector
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def vector_to_features(vector: typing.Sequence[float]) -> typing.Mapping[str, str]:
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"""Create mapping from phoneme feature vector"""
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features: typing.Dict[str, str] = {}
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for col_name, values in FEATURE_COLUMNS.items():
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col_key = FEATURE_KEYS[col_name]
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if col_name in FEATURE_ORDINAL_COLUMNS:
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# Single value normalized by number of possible values
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assert isinstance(col_key, int)
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val_idx = int(vector[col_key] * len(values))
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else:
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# One-hot vector
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assert isinstance(col_key, slice)
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if 1.0 not in vector[col_key]:
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assert False, (col_name, col_key, vector[col_key])
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val_idx = vector[col_key].index(1.0)
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features[col_name] = values[val_idx]
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return features
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