(synthesizing_speech)= # Synthesizing Speech First, you need to install TTS. We recommend using PyPi. You need to call the command below: ```bash $ pip install TTS ``` After the installation, 2 terminal commands are available. 1. TTS Command Line Interface (CLI). - `tts` 2. Local Demo Server. - `tts-server` 3. In 🐍Python. - `from TTS.api import TTS` ## On the Commandline - `tts` ![cli.gif](https://github.com/coqui-ai/TTS/raw/main/images/tts_cli.gif) After the installation, 🐸TTS provides a CLI interface for synthesizing speech using pre-trained models. You can either use your own model or the release models under 🐸TTS. Listing released 🐸TTS models. ```bash tts --list_models ``` Run a TTS model, from the release models list, with its default vocoder. (Simply copy and paste the full model names from the list as arguments for the command below.) ```bash tts --text "Text for TTS" \ --model_name "///" \ --out_path folder/to/save/output.wav ``` Run a tts and a vocoder model from the released model list. Note that not every vocoder is compatible with every TTS model. ```bash tts --text "Text for TTS" \ --model_name "tts_models///" \ --vocoder_name "vocoder_models///" \ --out_path folder/to/save/output.wav ``` Run your own TTS model (Using Griffin-Lim Vocoder) ```bash tts --text "Text for TTS" \ --model_path path/to/model.pth \ --config_path path/to/config.json \ --out_path folder/to/save/output.wav ``` Run your own TTS and Vocoder models ```bash tts --text "Text for TTS" \ --config_path path/to/config.json \ --model_path path/to/model.pth \ --out_path folder/to/save/output.wav \ --vocoder_path path/to/vocoder.pth \ --vocoder_config_path path/to/vocoder_config.json ``` Run a multi-speaker TTS model from the released models list. ```bash tts --model_name "tts_models///" --list_speaker_idxs # list the possible speaker IDs. tts --text "Text for TTS." --out_path output/path/speech.wav --model_name "tts_models///" --speaker_idx "" ``` Run a released voice conversion model ```bash tts --model_name "voice_conversion///" --source_wav "my/source/speaker/audio.wav" --target_wav "my/target/speaker/audio.wav" --out_path folder/to/save/output.wav ``` **Note:** You can use ```./TTS/bin/synthesize.py``` if you prefer running ```tts``` from the TTS project folder. ## On the Demo Server - `tts-server` ![server.gif](https://github.com/coqui-ai/TTS/raw/main/images/demo_server.gif) You can boot up a demo 🐸TTS server to run an inference with your models. Note that the server is not optimized for performance but gives you an easy way to interact with the models. The demo server provides pretty much the same interface as the CLI command. ```bash tts-server -h # see the help tts-server --list_models # list the available models. ``` Run a TTS model, from the release models list, with its default vocoder. If the model you choose is a multi-speaker TTS model, you can select different speakers on the Web interface and synthesize speech. ```bash tts-server --model_name "///" ``` Run a TTS and a vocoder model from the released model list. Note that not every vocoder is compatible with every TTS model. ```bash tts-server --model_name "///" \ --vocoder_name "///" ``` ## Python 🐸TTS API You can run a multi-speaker and multi-lingual model in Python as ```python import torch from TTS.api import TTS # Get device device = "cuda" if torch.cuda.is_available() else "cpu" # List available 🐸TTS models print(TTS().list_models()) # Init TTS tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to(device) # Run TTS # ❗ Since this model is multi-lingual voice cloning model, we must set the target speaker_wav and language # Text to speech list of amplitude values as output wav = tts.tts(text="Hello world!", speaker_wav="my/cloning/audio.wav", language="en") # Text to speech to a file tts.tts_to_file(text="Hello world!", speaker_wav="my/cloning/audio.wav", language="en", file_path="output.wav") ``` #### Here is an example for a single speaker model. ```python # Init TTS with the target model name tts = TTS(model_name="tts_models/de/thorsten/tacotron2-DDC", progress_bar=False) # Run TTS tts.tts_to_file(text="Ich bin eine Testnachricht.", file_path=OUTPUT_PATH) ``` #### Example voice cloning with YourTTS in English, French and Portuguese: ```python tts = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", progress_bar=False).to("cuda") tts.tts_to_file("This is voice cloning.", speaker_wav="my/cloning/audio.wav", language="en", file_path="output.wav") tts.tts_to_file("C'est le clonage de la voix.", speaker_wav="my/cloning/audio.wav", language="fr", file_path="output.wav") tts.tts_to_file("Isso é clonagem de voz.", speaker_wav="my/cloning/audio.wav", language="pt", file_path="output.wav") ``` #### Example voice conversion converting speaker of the `source_wav` to the speaker of the `target_wav` ```python tts = TTS(model_name="voice_conversion_models/multilingual/vctk/freevc24", progress_bar=False).to("cuda") tts.voice_conversion_to_file(source_wav="my/source.wav", target_wav="my/target.wav", file_path="output.wav") ``` #### Example voice cloning by a single speaker TTS model combining with the voice conversion model. This way, you can clone voices by using any model in 🐸TTS. ```python tts = TTS("tts_models/de/thorsten/tacotron2-DDC") tts.tts_with_vc_to_file( "Wie sage ich auf Italienisch, dass ich dich liebe?", speaker_wav="target/speaker.wav", file_path="ouptut.wav" ) ``` #### Example text to speech using **Fairseq models in ~1100 languages** 🤯. For these models use the following name format: `tts_models//fairseq/vits`. You can find the list of language ISO codes [here](https://dl.fbaipublicfiles.com/mms/tts/all-tts-languages.html) and learn about the Fairseq models [here](https://github.com/facebookresearch/fairseq/tree/main/examples/mms). ```python from TTS.api import TTS api = TTS(model_name="tts_models/eng/fairseq/vits").to("cuda") api.tts_to_file("This is a test.", file_path="output.wav") # TTS with on the fly voice conversion api = TTS("tts_models/deu/fairseq/vits") api.tts_with_vc_to_file( "Wie sage ich auf Italienisch, dass ich dich liebe?", speaker_wav="target/speaker.wav", file_path="ouptut.wav" ) ```