Espeak phonemizer pipeline for spanish (and also english)

tts/text/pipeline/espeak_pipeline.py

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+from typing import List
+from text.pipeline.base_pipeline import BasePipeline
+from text.pipeline_components.input_parsing.parser import ArpabetSequence, GraphemeSequence, ParsedSequence, parse_grapheme_and_arpabet_sequence
+from text.pipeline_components.normalization.espeak_normalization import normalize
+from text.pipeline_components.phonetization.espeak_phonemization import EspeakPhonetization
+from text.pipeline_components.sequencing.espeak_symbols import Symbols
+
+class EspeakPipeline(BasePipeline):
+    """
+    This is a new text pipeline for FakeYou that will be introduced in July 2022.
+    It introduces Arpabet and individually upgradable components.
+    The code is not 1:1 with our notebooks, but we'll go to efforts to make sure that 
+    the model input expectations on both sides match one another.
+    """
+
+    def __init__(self, lang='en'):
+        self.lang = lang
+        symbols = Symbols(lang)
+        self.symbols_to_sequence = symbols.symbols_to_sequence
+        self.arpabet_to_sequence = symbols.arpabet_to_sequence
+        self.sequence_to_text = symbols.sequence_to_text
+        self.SPACE_INTEGER_ENCODING = symbols.SPACE_INTEGER_ENCODING
+
+        self.phonetization = EspeakPhonetization(lang)
+
+    def user_input_to_sequence(self, input_text: str) -> List[int]:
+        """Convert raw user input into a numerical sequence for ML inference."""
+
+        parsed_sequence = parse_grapheme_and_arpabet_sequence(input_text)
+        self._normalize_graphemes(parsed_sequence)
+
+        parsed_sequence = self._convert_phonemes(parsed_sequence)
+        
+        return self._convert_to_integer_sequence(parsed_sequence)
+
+    def sequence_to_text(self, input_sequence: List[int]) -> str:
+        return self.sequence_to_text(input_sequence)
+
+    def _normalize_graphemes(self, parsed_sequence: ParsedSequence):
+        for i in range(len(parsed_sequence)):
+            subsequence = parsed_sequence[i]
+            if isinstance(subsequence, GraphemeSequence):
+                normalized = normalize(subsequence.sequence, self.lang)
+                parsed_sequence[i] = GraphemeSequence(normalized)
+
+
+    def _convert_phonemes(self, parsed_sequence: ParsedSequence) -> ParsedSequence:
+        # NB: We will likely break grapheme runs into multiple arpabet sequences, extending the 
+        # output list length.
+        updated_sequence = []
+
+        for subsequence in parsed_sequence:
+            if isinstance(subsequence, ArpabetSequence):
+                updated_sequence.append(subsequence)
+
+            elif isinstance(subsequence, GraphemeSequence):
+                converted_sequence = self.phonetization.try_convert_to_phonemes(subsequence.sequence)
+                updated_sequence.extend(converted_sequence)
+
+        return updated_sequence
+
+    def _convert_to_integer_sequence(self, parsed_sequence: ParsedSequence) -> List[int]:
+        integer_sequence = []
+        last_index = len(parsed_sequence) - 1
+
+        for i, subsequence in enumerate(parsed_sequence):
+            integer_subsequence = []
+
+            if isinstance(subsequence, ArpabetSequence):
+                integer_subsequence = self.arpabet_to_sequence(subsequence.sequence)
+            elif isinstance(subsequence, GraphemeSequence):
+                integer_subsequence = self.symbols_to_sequence(subsequence.sequence)
+                
+            if integer_subsequence:
+                integer_sequence.extend(integer_subsequence)
+
+                if i < last_index and integer_sequence[-1] != self.SPACE_INTEGER_ENCODING:
+                    # Separate words with single spaces if not already present.
+                    integer_sequence.append(self.SPACE_INTEGER_ENCODING)
+
+        return integer_sequence