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a/pyproject.toml b/pyproject.toml index 2c98a3d..911d442 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -13,6 +13,7 @@ packages = [ [tool.poetry.dependencies] python = "~3.11" setuptools= ">=77" +coqui-tts = "0.26" [tool.poetry.group.general.dependencies] requests="2.32.3" @@ -36,7 +37,7 @@ auracast = { git = "ssh://git@ssh.pstruebi.xyz:222/auracaster/bumble-auracast.gi [tool.poetry.group.dev.dependencies] -pytest = ">8.2" +pytest = {version=">8.2", optional=true} [tool.pytest.ini_options] addopts = [ diff --git a/src/translator_models/translator_models.py b/src/translator_models/translator_models.py index 938c30c..a004c31 100644 --- a/src/translator_models/translator_models.py +++ b/src/translator_models/translator_models.py @@ -35,12 +35,18 @@ class TranslatorLangConfig(BaseModel): # llm_host_url: str | None = 'http://localhost:11434' # llm_host_token: str | None = None - tts_system: str = 'piper' - tts_model: str ='de_DE-kerstin-low' + tts_system: str = 'piper' # Options: 'piper', 'xtts' + tts_model: str = 'de_DE-kerstin-low' # For piper: model name, for xtts: unused + tts_language: str = 'de' # Language code for XTTS + tts_speaker: Optional[str] = None # Speaker name for XTTS class TranslatorConfig(BaseModel): - deu: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'de_DE-thorsten-high') + deu: TranslatorLangConfig = TranslatorLangConfig( + tts_system='xtts', + tts_language='de', + tts_speaker='Annmarie Nele' + ) eng: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'en_GB-alba-medium') fra: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'fr_FR-siwis-medium') spa: TranslatorLangConfig = TranslatorLangConfig(tts_model = 'es_ES-sharvard-medium') diff --git a/src/voice_models/request_models.py b/src/voice_models/request_models.py index 69edbc0..f20d76f 100644 --- a/src/voice_models/request_models.py +++ b/src/voice_models/request_models.py @@ -1,4 +1,5 @@ from pydantic import BaseModel +from typing import Optional class SynthesizeRequest(BaseModel): text: str @@ -6,4 +7,6 @@ class SynthesizeRequest(BaseModel): framework: str = "piper" model: str = "en_US-lessac-medium" return_lc3: bool = False - + language: str = "en" # Language code for XTTS + speaker: Optional[str] = None # Speaker name for XTTS + speaker_wav: Optional[str] = None # Path to speaker sample for XTTS voice cloning diff --git a/src/voice_provider/text_to_speech.py b/src/voice_provider/text_to_speech.py index 2a4611f..a530b8f 100644 --- a/src/voice_provider/text_to_speech.py +++ b/src/voice_provider/text_to_speech.py @@ -1,4 +1,7 @@ import os +# Set environment variable to auto-accept Coqui TTS license +os.environ["COQUI_TOS_AGREED"] = "1" + import shutil import subprocess import time @@ -6,9 +9,28 @@ import json import logging as log import numpy as np import asyncio +import torch from voice_provider.utils.resample import resample_array from voice_provider.utils.encode_lc3 import encode_lc3 +# Now import TTS - the license will be auto-accepted +from TTS.api import TTS + +# Get device for XTTS +if torch.cuda.is_available(): + log.info('XTTS will run on GPU') + XTTS_DEVICE = "cuda" +else: + log.info('XTTS will run on CPU') + XTTS_DEVICE = "cpu" + +# Load XTTS model globally - only once +log.info("Initializing XTTS model...") +start_init = time.time() +XTTS_MODEL = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to(XTTS_DEVICE) +end_init = time.time() +log.info(f"XTTS initialization completed in {end_init - start_init:.2f} seconds") + PIPER_EXE = shutil.which('piper') TTS_DIR = os.path.join(os.path.dirname(__file__)) @@ -26,7 +48,7 @@ def synth_piper(text, model="en_US-lessac-medium"): ret = subprocess.run( # TODO: wrap this whole thing in a class and open a permanent pipe to the model [ PIPER_EXE, - '--cuda', + #'--cuda', '--model', model, '--output-raw' ], @@ -52,7 +74,10 @@ def synthesize( target_sample_rate, framework, model="en_US-lessac-medium", - return_lc3=True + return_lc3=True, + language="en", + speaker=None, + speaker_wav=None ): if framework == 'piper': @@ -64,7 +89,38 @@ def synthesize( elif framework == 'koro': pass elif framework == 'xtts': - pass + start = time.time() + + # Generate audio using XTTS + # XTTS always outputs at 24kHz + xtts_sample_rate = 24000 + + # Validate speaker parameters - XTTS needs either speaker or speaker_wav + if speaker is None and speaker_wav is None: + # Use the first available speaker if none specified + speaker = XTTS_MODEL.speakers[0] + log.info(f"No speaker specified, using default: {speaker}") + + # Generate audio samples using tts.tts + if speaker_wav: + log.info(f"Generating XTTS audio with speaker_wav: {speaker_wav}") + audio_list = XTTS_MODEL.tts(text=text, speaker_wav=speaker_wav, language=language) + else: + log.info(f"Generating XTTS audio with speaker: {speaker}") + audio_list = XTTS_MODEL.tts(text=text, speaker=speaker, language=language) + + # Ensure audio_np is a numpy array and properly scaled + audio_np = np.array(audio_list, dtype=np.float32)# / (2**15-1) + + # Log some info about the audio data + log.info(f"XTTS audio shape: {audio_np.shape}, dtype: {audio_np.dtype}, " + f"min: {audio_np.min():.4f}, max: {audio_np.max():.4f}") + + # Resample from 24kHz to target sample rate with speedup factor + audio = resample_array(audio_np, xtts_sample_rate, target_sample_rate, speedup=1.05) + + log.info(f"XTTS synthesis completed in {time.time() - start:.2f} seconds") + elif framework == 'zonos': pass else: raise NotImplementedError('unknown framework') @@ -82,7 +138,10 @@ async def synthesize_async( target_sample_rate, framework, model="en_US-lessac-medium", - return_lc3=True + return_lc3=True, + language="en", + speaker=None, + speaker_wav=None ): """ Asynchronous version of the synthesize function that runs in a thread pool. @@ -90,9 +149,12 @@ async def synthesize_async( Args: text: Text to synthesize target_sample_rate: Target sample rate for the audio - framework: TTS framework to use (e.g., 'piper') + framework: TTS framework to use (e.g., 'piper', 'xtts') model: Model to use for synthesis return_lc3: Whether to return LC3-encoded audio + language: Language code (used by XTTS) + speaker: Speaker ID for XTTS + speaker_wav: Path to speaker sample for XTTS voice cloning Returns: LC3-encoded audio as string or raw audio as numpy array @@ -101,23 +163,64 @@ async def synthesize_async( loop = asyncio.get_event_loop() result = await loop.run_in_executor( None, - lambda: synthesize(text, target_sample_rate, framework, model, return_lc3) + lambda: synthesize( + text, + target_sample_rate, + framework, + model, + return_lc3, + language, + speaker, + speaker_wav + ) ) return result if __name__ == '__main__': - import logging import soundfile as sf - logging.basicConfig( - level=logging.INFO, + log.basicConfig( + level=log.INFO, format='%(module)s.py:%(lineno)d %(levelname)s: %(message)s' ) - target_rate=16000 + target_rate = 16000 - audio = synthesize('Hello World', target_rate, 'piper', model= 'de_DE-kerstin-low', return_lc3=False) + # First, print available XTTS speakers + print("Available XTTS speakers:") + print(XTTS_MODEL.speakers) + + # Demo of Piper + print("Testing Piper TTS...") + audio_piper = synthesize('Hello World', target_rate, 'piper', model='de_DE-kerstin-low', return_lc3=False) + sf.write('hello_piper.wav', audio_piper, target_rate) - sf.write('hello.wav', audio, target_rate) + # Demo of XTTS with Annmarie Nele for German + german_speaker = 'Annmarie Nele' + print(f"Testing XTTS with German language using speaker: {german_speaker}") + text_to_synthesize = "Dies ist ein Test der XTTS Stimme auf Deutsch mit Annmarie Nele als Sprecherin." + + audio_xtts = synthesize( + text=text_to_synthesize, + target_sample_rate=target_rate, + framework='xtts', + language='de', + speaker=german_speaker, + return_lc3=False + ) + + # Save the wav file + sf.write('hello_xtts_german.wav', audio_xtts, target_rate) + + # Also test with LC3 encoding + lc3_xtts = synthesize( + text=text_to_synthesize, + target_sample_rate=target_rate, + framework='xtts', + language='de', + speaker=german_speaker, + return_lc3=True + ) + print(f"Generated LC3 data length: {len(lc3_xtts)} bytes") print('Done.') diff --git a/src/voice_provider/tts_server.py b/src/voice_provider/tts_server.py index 6ce8fe1..d430338 100644 --- a/src/voice_provider/tts_server.py +++ b/src/voice_provider/tts_server.py @@ -17,7 +17,10 @@ async def synthesize_speech(request: SynthesizeRequest): target_sample_rate=request.target_sample_rate, framework=request.framework, model=request.model, - return_lc3=request.return_lc3 + return_lc3=request.return_lc3, + language=request.language, + speaker=request.speaker, + speaker_wav=request.speaker_wav ) if request.return_lc3: diff --git a/src/voice_provider/utils/resample.py b/src/voice_provider/utils/resample.py index 56f41d7..9d26ef3 100644 --- a/src/voice_provider/utils/resample.py +++ b/src/voice_provider/utils/resample.py @@ -24,20 +24,29 @@ def resample_file(filename, out_filename, target_rate): log.info("Resampling of %s took %s s", os.path.basename(filename), round(time.time() - start, 3)) -def resample_array(audio, rate, target_rate): +def resample_array(audio, rate, target_rate, speedup=1.0): start=time.time() # Load the original audio file - if rate == target_rate: # Nothing to do - log.info('audio already at target rate, skipping resample') + if rate == target_rate and speedup == 1.0: # Nothing to do + log.info('audio already at target rate with no speedup, skipping resample') return audio + # Apply speedup if needed + if speedup != 1.0: + # When speeding up, we need to resample to a lower rate first + # This effectively shortens the audio duration + effective_orig_sr = rate * speedup + log.info(f"Applying speedup factor of {speedup}") + else: + effective_orig_sr = rate + # Convert the sample rate to target rate - resampled_audio = librosa.resample(audio, orig_sr=rate, target_sr=target_rate) + resampled_audio = librosa.resample(audio, orig_sr=effective_orig_sr, target_sr=target_rate) # Save the resampled audio as a new .wav file - log.info("Resampling took %s s", round(time.time() - start, 3)) + log.info("Resampling took %s s", round(time.time() - start, 3)) return resampled_audio