utils/tts_dummy.py

import logging
import os
import time
import numpy as np
import soundfile as sf
from typing import Optional, Generator, Tuple, List
from .tts_base import TTSBase

# Configure logging
logger = logging.getLogger(__name__)


class DummyTTS(TTSBase):
    """Dummy TTS engine that generates sine wave audio
    
    This class is used as a fallback when no other TTS engine is available.
    """
    
    def generate_speech(self, text: str, voice: str = 'default', speed: float = 1.0) -> str:
        """Generate a dummy sine wave audio file
        
        Args:
            text (str): Input text (not used)
            voice (str): Voice ID (not used)
            speed (float): Speech speed multiplier (not used)
            
        Returns:
            str: Path to the generated audio file
        """
        logger.info(f"Generating dummy speech for text length: {len(text)}")
        
        # Generate a simple sine wave
        sample_rate = 24000
        duration = min(len(text) / 20, 10)  # Rough approximation of speech duration
        t = np.linspace(0, duration, int(sample_rate * duration), endpoint=False)
        audio = 0.5 * np.sin(2 * np.pi * 440 * t)  # 440 Hz sine wave
        
        # Save to file
        output_path = self._generate_output_path(prefix="dummy")
        sf.write(output_path, audio, sample_rate)
        
        logger.info(f"Generated dummy audio: {output_path}")
        return output_path
    
    def generate_speech_stream(self, text: str, voice: str = 'default', speed: float = 1.0) -> Generator[Tuple[int, np.ndarray], None, None]:
        """Generate a dummy sine wave audio stream
        
        Args:
            text (str): Input text (not used)
            voice (str): Voice ID (not used)
            speed (float): Speech speed multiplier (not used)
            
        Yields:
            tuple: (sample_rate, audio_data) pairs
        """
        logger.info(f"Generating dummy speech stream for text length: {len(text)}")
        
        # Generate a simple sine wave
        sample_rate = 24000
        duration = min(len(text) / 20, 10)  # Rough approximation of speech duration
        t = np.linspace(0, duration, int(sample_rate * duration), endpoint=False)
        audio = 0.5 * np.sin(2 * np.pi * 440 * t)  # 440 Hz sine wave
        
        # Yield the audio data
        yield sample_rate, audio