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| """ | |
| Notes | |
| ----- | |
| This module contains the functions for audiobook_gen that handle text-to-speech generation. | |
| The functions take in the preprocessed text and invoke the Silero package to generate audio tensors. | |
| """ | |
| import logging | |
| import torch | |
| from stqdm import stqdm | |
| from src import output, config | |
| def load_model(): | |
| """ | |
| Load Silero package containg the model information | |
| for the language and speaker set in config.py | |
| and converts it to the set device. | |
| Parameters | |
| ---------- | |
| None | |
| Returns | |
| ------- | |
| model : torch.package | |
| """ | |
| from silero import silero_tts | |
| model, _ = silero_tts(language=config.LANGUAGE, speaker=config.MODEL_ID) | |
| model.to(config.DEVICE) | |
| return model | |
| def generate_audio(corpus, title, model, speaker): | |
| """ | |
| For each section within the corpus, calls predict() function to generate audio tensors | |
| and then calls write_audio() to output the tensors to audio files. | |
| Parameters | |
| ---------- | |
| corpus : array_like | |
| list of list of strings, | |
| body of tokenized text from which audio is generated | |
| title : str | |
| title of document, used to name output files | |
| model : torch.package | |
| torch package containing model for language and speaker specified | |
| speaker : str | |
| identifier of selected speaker for audio generation | |
| Returns | |
| ------- | |
| None | |
| """ | |
| for section in stqdm(corpus, desc="Sections in document:"): | |
| section_index = f'part{corpus.index(section):03}' | |
| audio_list, sample_path = predict(section, section_index, title, model, speaker) | |
| output.write_audio(audio_list, sample_path) | |
| def predict(text_section, section_index, title, model, speaker): | |
| """ | |
| Applies Silero TTS engine for each token within the corpus section, | |
| appending it to the output tensor array, and creates file path for output. | |
| Parameters | |
| ---------- | |
| text_section : array_like | |
| list of strings, | |
| body of tokenized text from which audio is generated | |
| section_index : int | |
| index of current section within corpus | |
| title : str | |
| title of document, used to name output files | |
| model : torch.package | |
| torch package containing model for language and speaker specified | |
| speaker : str | |
| identifier of selected speaker for audio generation | |
| Returns | |
| ------- | |
| audio_list : torch.tensor | |
| pytorch tensor containing generated audio | |
| sample_path : str | |
| file name and path for outputting tensor to audio file | |
| """ | |
| audio_list = [] | |
| for sentence in stqdm(text_section, desc="Sentences in section:"): | |
| audio = model.apply_tts(text=sentence, speaker=speaker, sample_rate=config.SAMPLE_RATE) | |
| if len(audio) > 0 and isinstance(audio, torch.Tensor): | |
| audio_list.append(audio) | |
| logging.info(f'Tensor generated for sentence: \n {sentence}') | |
| else: | |
| logging.info(f'Tensor for sentence is not valid: \n {sentence}') | |
| sample_path = config.output_path / f'{title}_{section_index}.wav' | |
| return audio_list, sample_path | |