Implement cloning in API

TTS/api.py

@@ -33,6 +33,12 @@ class TTS:
             >>> tts = TTS(model_path="/path/to/checkpoint_100000.pth", config_path="/path/to/config.json", progress_bar=False, gpu=False)
             >>> tts.tts_to_file(text="Ich bin eine Testnachricht.", file_path="output.wav")
 
+        Example voice cloning with YourTTS in English, French and Portuguese:
+            >>> tts = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", progress_bar=False, gpu=True)
+            >>> tts.tts_to_file("This is voice cloning.", speaker_wav="my/cloning/audio.wav", language="en", file_path="thisisit.wav")
+            >>> tts.tts_to_file("C'est le clonage de la voix.", speaker_wav="my/cloning/audio.wav", language="fr", file_path="thisisit.wav")
+            >>> tts.tts_to_file("Isso é clonagem de voz.", speaker_wav="my/cloning/audio.wav", language="pt", file_path="thisisit.wav")
+
         Args:
             model_name (str, optional): Model name to load. You can list models by ```tts.models```. Defaults to None.
             model_path (str, optional): Path to the model checkpoint. Defaults to None.
@@ -144,8 +150,8 @@ class TTS:
             use_cuda=gpu,
         )
 
-    def _check_arguments(self, speaker: str = None, language: str = None):
-        if self.is_multi_speaker and speaker is None:
+    def _check_arguments(self, speaker: str = None, language: str = None, speaker_wav: str = None):
+        if self.is_multi_speaker and (speaker is None and speaker_wav is None):
             raise ValueError("Model is multi-speaker but no speaker is provided.")
         if self.is_multi_lingual and language is None:
             raise ValueError("Model is multi-lingual but no language is provided.")
@@ -154,7 +160,7 @@ class TTS:
         if not self.is_multi_lingual and language is not None:
             raise ValueError("Model is not multi-lingual but language is provided.")
 
-    def tts(self, text: str, speaker: str = None, language: str = None):
+    def tts(self, text: str, speaker: str = None, language: str = None, speaker_wav: str = None):
         """Convert text to speech.
 
         Args:
@@ -166,14 +172,17 @@ class TTS:
             language (str, optional):
                 Language code for multi-lingual models. You can check whether loaded model is multi-lingual
                 `tts.is_multi_lingual` and list available languages by `tts.languages`. Defaults to None.
+            speaker_wav (str, optional):
+                Path to a reference wav file to use for voice cloning with supporting models like YourTTS.
+                Defaults to None.
         """
-        self._check_arguments(speaker=speaker, language=language)
+        self._check_arguments(speaker=speaker, language=language, speaker_wav=speaker_wav)
 
         wav = self.synthesizer.tts(
             text=text,
             speaker_name=speaker,
             language_name=language,
-            speaker_wav=None,
+            speaker_wav=speaker_wav,
             reference_wav=None,
             style_wav=None,
             style_text=None,
@@ -181,7 +190,14 @@ class TTS:
         )
         return wav
 
-    def tts_to_file(self, text: str, speaker: str = None, language: str = None, file_path: str = "output.wav"):
+    def tts_to_file(
+        self,
+        text: str,
+        speaker: str = None,
+        language: str = None,
+        speaker_wav: str = None,
+        file_path: str = "output.wav",
+    ):
         """Convert text to speech.
 
         Args:
@@ -193,8 +209,11 @@ class TTS:
             language (str, optional):
                 Language code for multi-lingual models. You can check whether loaded model is multi-lingual
                 `tts.is_multi_lingual` and list available languages by `tts.languages`. Defaults to None.
+            speaker_wav (str, optional):
+                Path to a reference wav file to use for voice cloning with supporting models like YourTTS.
+                Defaults to None.
             file_path (str, optional):
                 Output file path. Defaults to "output.wav".
         """
-        wav = self.tts(text=text, speaker=speaker, language=language)
+        wav = self.tts(text=text, speaker=speaker, language=language, speaker_wav=speaker_wav)
         self.synthesizer.save_wav(wav=wav, path=file_path)

TTS/utils/synthesizer.py

@@ -187,7 +187,7 @@ class Synthesizer(object):
             text (str): input text.
             speaker_name (str, optional): spekaer id for multi-speaker models. Defaults to "".
             language_name (str, optional): language id for multi-language models. Defaults to "".
-            speaker_wav (Union[str, List[str]], optional): path to the speaker wav. Defaults to None.
+            speaker_wav (Union[str, List[str]], optional): path to the speaker wav for voice cloning. Defaults to None.
             style_wav ([type], optional): style waveform for GST. Defaults to None.
             style_text ([type], optional): transcription of style_wav for Capacitron. Defaults to None.
             reference_wav ([type], optional): reference waveform for voice conversion. Defaults to None.

tests/inference_tests/test_python_api.py

@@ -1,10 +1,12 @@
 import os
 import unittest
 
-from tests import get_tests_output_path
+from tests import get_tests_data_path, get_tests_output_path
+
 from TTS.api import TTS
 
 OUTPUT_PATH = os.path.join(get_tests_output_path(), "test_python_api.wav")
+cloning_test_wav_path = os.path.join(get_tests_data_path(), "ljspeech/wavs/LJ001-0028.wav")
 
 
 class TTSTest(unittest.TestCase):
@@ -34,3 +36,8 @@ class TTSTest(unittest.TestCase):
         self.assertTrue(tts.is_multi_lingual)
         self.assertGreater(len(tts.speakers), 1)
         self.assertGreater(len(tts.languages), 1)
+
+    def test_voice_cloning():
+        tts = TTS()
+        tts.load_model_by_name("tts_models/multilingual/multi-dataset/your_tts")
+        tts.tts_to_file("Hello world!", speaker_wav=cloning_test_wav_path, language="en", file_path=OUTPUT_PATH)