(self, cache_extension: str, model: str, language: Languages)

( engine_error_rate: Dict[Engines, Dict[Datasets, float]], save_path: str, streaming: bool, sh

(self, index: int)

(self, sentence: str, raise_error_on_invalid_sentence: bool)

(x: str)

(self, language: Languages, punctuation: bool, dataset_name: str)

(cls, x: Metrics)

(self, path: str)

(self, event)

(self)

(self)

(self, path: str)

(self)

(tokens: Sequence[str], punctuation: str)

(self, evt: SpeechRecognitionEventArgs)

(self, changed_words)

(new_words: Sequence[str], time: float, emitted_words: List[str], receive_timings: List[float])

(cls, x: Engines, language: Languages, **kwargs)

( self, path: str, alignments: Optional[Sequence[Tuple[float, float]]] )

(sentence: str)

(self)

(sentence: str)

( dp: NDArray, reference: Sequence[str], prediction: Sequence[str], reference_

( dp: Sequence[Sequence[int]], row: int, col: int, ref_words: Sequence[str], pred_words: Sequence[str]

(reference: Sequence[str], prediction: Sequence[str])

( reference_words: Sequence[str], predicted_words: Sequence[str] )

(folder: str, normalizer: Normalizer)

(folder: str, normalizer: Normalizer)

( self, path: str, alignments: Optional[Sequence[Tuple[float, float]]] )

( self, path: str, alignments: Optional[Sequence[Tuple[float, float]]] )

(save_folder: str, show: bool, dataset: Datasets = Datasets.TED_LIUM)

(save_folder: str, show: bool)

(save_folder: str, show: bool)

(save_folder: str, show: bool)

(save_folder: str, show: bool, dataset: Datasets = Datasets.LIBRI_SPEECH_TEST_CLEAN)

(self, result)

(self, s: str)

(word1: str, word2: str)

( self, ref_timings: Sequence[float], pred_timings: Sequence[float], aligned_words: Sequence[Tuple[str

( self, ref_words: Sequence[str], pred_words: Sequence[str], max_errors_skip_threshold: int = 20 )

(self)

(self, prediction: str, reference: str)

(language: Languages, download_folder: str)

(indices: Sequence[int], dataset: Dataset, output_folder: str, num_workers: int)

(self)

(dataset_folder: str)

()

()

()

()

(textgrid_file: str)

(indices: Sequence[int], dataset: Dataset, corpus_folder: str)

(self)

(corpus_folder: str, work_folder: str, num_workers: int)

(self)

(self, folder: str, language: Languages, punctuation: bool, normalizer: Normalizer)

( self, folder: str, language: Languages, punctuation: bool, normalize

( self, folder: str, language: Languages, punctuation: bool, normalize

( self, folder: str, language: Languages, punctuation: bool, normalizer: Normalizer, split_audio: bool

(self, folder: str, language: Languages, punctuation: bool, normalizer: Normalizer)

(self, folder: str, language: Languages, punctuation: bool, normalizer: Normalizer)

(self, folder: str, language: Languages, punctuation: bool, normalizer: Normalizer)

(self, keep_punctuation: bool, punctuation_set: str = SUPPORTED_PUNCTUATION_SET)

(self, language: Languages, aws_location: str = "us-west-2")

( self, language: Languages, apply_delay: bool, ignore_punctuation: bool,

(self, transcript_result_stream: TranscriptResultStream, ignore_punctuation: bool)

( self, azure_speech_key: str, azure_speech_location: str, language: Languages

( self, language: Languages, apply_delay: bool, ignore_punctuation: bool,

(self, ignore_punctuation: bool)

( self, language: Languages, cache_extension: str = ".ggl", model: Optional[st

(self, language: Languages)

( self, language: Languages, apply_delay: bool, ignore_punctuation: bool,

( self, language: Languages, apply_delay: bool, ignore_punctuation: bool,

( self, pcm: ByteString, word_timings: Sequence[float], chunk_size_bytes: int,

(self, ignore_punctuation: bool)

( self, watson_speech_to_text_api_key: str, watson_speech_to_text_url: str, la

(self, language: Languages)

(self, language: Languages)

(self, language: Languages)

(self, language: Languages)

(self, language: Languages)

(self, language: Languages)

(self, language: Languages)

(self, language: Languages)

( self, model_name: str, language: Languages, cache_extension: str, ch

(self, language: Languages, chunk_size_ms: Optional[int] = None, **kwargs)

(self, language: Languages, chunk_size_ms: Optional[int] = None, **kwargs)

(self, language: Languages, chunk_size_ms: Optional[int] = None, **kwargs)

(self, language: Languages, chunk_size_ms: Optional[int] = None, **kwargs)

(self, language: Languages, chunk_size_ms: Optional[int] = None, **kwargs)

(self, language: Languages, chunk_size_ms: Optional[int] = None, **kwargs)

(self, model_name: str, cache_extension: str, chunk_size_ms: Optional[int] = None)

(self, language: Languages, chunk_size_ms: Optional[int] = None, **kwargs)

(self, language: Languages, chunk_size_ms: Optional[int] = None, **kwargs)

( self, cache_extension: str, model: ModelArch, chunk_size_ms: Optional[float]

(self, ignore_punctuation: bool = True)

(self, language: Languages, chunk_size_ms: Optional[float] = None, **kwargs)

(self, language: Languages, chunk_size_ms: Optional[float] = None, **kwargs)

(self, language: Languages, chunk_size_ms: Optional[float] = None, **kwargs)

( self, access_key: str, model_path: Optional[str], library_path: Optional[str