□️ Tools for training new models and fine-tuning existing models in any language. |- speaker_encoder/ (Speaker Encoder models.□TTS is a library for advanced Text-to-Speech generation. |- bin/ (folder for all the executables.) Run your own multi-speaker TTS model: $ tts -text "Text for TTS" -out_path output/path/speech.wav -model_path path/to/model.pth -config_path path/to/config.json -speakers_file_path path/to/speaker.json -speaker_idx ĭirectory Structure |- notebooks/ (Jupyter Notebooks for model evaluation, parameter selection and data analysis.) Run the multi-speaker TTS model with the target speaker ID: $ tts -text "Text for TTS." -out_path output/path/speech.wav -model_name "//" -speaker_idx ![]() List the available speakers and choose a among them: $ tts -model_name "//" -list_speaker_idxs vocoder_path path/to/vocoder.pth -vocoder_config_path path/to/vocoder_config.json Run your own TTS and Vocoder models: $ tts -text "Text for TTS" -model_path path/to/model.pth -config_path path/to/config.json -out_path output/path/speech.wav Run your own TTS model (Using Griffin-Lim Vocoder): $ tts -text "Text for TTS" -model_path path/to/model.pth -config_path path/to/config.json -out_path output/path/speech.wav Run with specific TTS and vocoder models from the list: $ tts -text "Text for TTS" -model_name "///" -vocoder_name "///" -out_path output/path/speech.wavįor example: $ tts -text "Text for TTS" -model_name "tts_models/en/ljspeech/glow-tts" -vocoder_name "vocoder_models/en/ljspeech/univnet" -out_path output/path/speech.wav Run a TTS model with its default vocoder model: $ tts -text "Text for TTS" -model_name "///" -out_path output/path/speech.wavįor example: $ tts -text "Text for TTS" -model_name "tts_models/en/ljspeech/glow-tts" -out_path output/path/speech.wav Run TTS with default models: $ tts -text "Text for TTS" -out_path output/path/speech.wav $ tts -model_info_by_idx "/"įor example: $ tts -model_info_by_idx tts_models/3 The model_query_idx uses the corresponding idx from -list_models. $ tts -model_info_by_name vocoder_models/en/ljspeech/hifigan_v2 $ tts -model_info_by_name "///"įor example: $ tts -model_info_by_name tts_models/tr/common-voice/glow-tts The model_info_by_name uses the name as it from the -list_models. ![]() Get model info (for both tts_models and vocoder_models): tts_with_vc_to_file ( "Wie sage ich auf Italienisch, dass ich dich liebe?", speaker_wav = "target/speaker.wav", file_path = "output.wav" ) Command-line tts Single Speaker Models # TTS with on the fly voice conversion api = TTS ( "tts_models/deu/fairseq/vits" ) api. tts_to_file ( text = "Das ist ein Test.", file_path = OUTPUT_PATH, language = "de", speed = 1.0 ) Example text to speech using Fairseq models in ~1100 languages □.įor Fairseq models, use the following name format: tts_models//fairseq/vits.Īnd learn about the Fairseq models here. list_models () # Run TTS with emotion and speed control # Emotion control only works with V1 model tts. tts_to_file ( text = "This is a test.", file_path = OUTPUT_PATH, emotion = "Happy", speed = 1.5 ) # XTTS-multilingual models = TTS ( cs_api_model = "XTTS-multilingual" ). tts_to_file ( text = "This is a test.", file_path = OUTPUT_PATH ) # V1 model models = TTS ( cs_api_model = "V1" ). list_models () # Init TTS with the target studio speaker tts = TTS ( model_name = "coqui_studio/en/Torcull Diarmuid/coqui_studio", progress_bar = False ) # Run TTS tts. □TTS is tested on Ubuntu 18.04 with python >= 3.7, /coqui_studio # XTTS model models = TTS ( cs_api_model = "XTTS" ). You can also help us implement more models.
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