#!/usr/bin/env python3 """ Advanced Voice Processor - Revolutionary Voice Actor Capabilities Professional voice synthesis, emotion analysis, and character development """ import os import json import asyncio import requests import numpy as np import soundfile as sf import librosa from typing import Dict, List, Any, Optional import logging from dataclasses import dataclass import io import base64 logger = logging.getLogger(__name__) @dataclass class VoiceCharacter: name: str personality: Dict[str, Any] voice_id: str emotion_profile: Dict[str, float] speaking_style: str language: str = "en" class AdvancedVoiceProcessor: """Advanced voice processing with professional voice actor capabilities""" def __init__(self, elevenlabs_api_key: str): self.elevenlabs_api_key = elevenlabs_api_key self.characters = {} self.voice_cache = {} self.emotion_analyzer = self._init_emotion_analyzer() def _init_emotion_analyzer(self): """Initialize emotion analysis system""" return { "emotions": ["happy", "sad", "angry", "calm", "excited", "professional", "friendly", "serious"], "intensity_levels": ["low", "medium", "high"], "voice_mapping": { "happy": {"pitch_shift": 2, "speed": 1.1, "energy": 1.2}, "sad": {"pitch_shift": -2, "speed": 0.9, "energy": 0.8}, "angry": {"pitch_shift": 3, "speed": 1.2, "energy": 1.4}, "calm": {"pitch_shift": -1, "speed": 0.95, "energy": 0.9}, "excited": {"pitch_shift": 4, "speed": 1.3, "energy": 1.5}, "professional": {"pitch_shift": 0, "speed": 1.0, "energy": 1.0}, "friendly": {"pitch_shift": 1, "speed": 1.05, "energy": 1.1}, "serious": {"pitch_shift": -1, "speed": 0.9, "energy": 0.95} } } async def synthesize_voice(self, text: str, voice_id: str, emotion: str = "neutral", speed: float = 1.0, pitch: float = 0) -> bytes: """Synthesize voice with emotional expression""" try: url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}" headers = { "Accept": "audio/mpeg", "Content-Type": "application/json", "xi-api-key": self.elevenlabs_api_key } # Apply emotion-based voice settings emotion_settings = self.emotion_analyzer["voice_mapping"].get(emotion, {}) adjusted_speed = speed * emotion_settings.get("speed", 1.0) adjusted_pitch = pitch + emotion_settings.get("pitch_shift", 0) data = { "text": text, "model_id": "eleven_multilingual_v2", "voice_settings": { "stability": 0.5, "similarity_boost": 0.75, "style": 0.0, "use_speaker_boost": True } } response = requests.post(url, headers=headers, json=data) if response.status_code == 200: return response.content else: raise Exception(f"Voice synthesis failed: {response.status_code}") except Exception as e: logger.error(f"Voice synthesis error: {e}") raise def create_character(self, name: str, personality: Dict[str, Any], voice_id: str, language: str = "en") -> VoiceCharacter: """Create a new voice character with personality""" character = VoiceCharacter( name=name, personality=personality, voice_id=voice_id, emotion_profile=self._analyze_personality_emotions(personality), speaking_style=personality.get("speaking_style", "neutral"), language=language ) self.characters[name] = character return character def _analyze_personality_emotions(self, personality: Dict[str, Any]) -> Dict[str, float]: """Analyze personality traits to determine emotion profile""" traits = personality.get("traits", []) emotion_profile = { "happy": 0.5, "sad": 0.5, "angry": 0.5, "calm": 0.5, "excited": 0.5, "professional": 0.5, "friendly": 0.5, "serious": 0.5 } # Map personality traits to emotions trait_emotion_mapping = { "intelligent": {"professional": 0.8, "serious": 0.7}, "friendly": {"friendly": 0.9, "happy": 0.7}, "energetic": {"excited": 0.9, "happy": 0.8}, "serious": {"serious": 0.9, "professional": 0.8}, "calm": {"calm": 0.9, "professional": 0.7}, "enthusiastic": {"excited": 0.8, "happy": 0.8}, "helpful": {"friendly": 0.8, "professional": 0.7} } for trait in traits: if trait in trait_emotion_mapping: for emotion, value in trait_emotion_mapping[trait].items(): emotion_profile[emotion] = max(emotion_profile[emotion], value) return emotion_profile async def speak_as_character(self, character_name: str, dialogue: str, emotion: Optional[str] = None) -> bytes: """Generate speech in character's voice with appropriate emotion""" if character_name not in self.characters: raise ValueError(f"Character '{character_name}' not found") character = self.characters[character_name] # Determine emotion if not specified if emotion is None: emotion = self._detect_emotion_from_text(dialogue) # Adjust emotion based on character's personality adjusted_emotion = self._adjust_emotion_for_character(character, emotion) return await self.synthesize_voice( text=dialogue, voice_id=character.voice_id, emotion=adjusted_emotion ) def _detect_emotion_from_text(self, text: str) -> str: """Detect emotion from text content""" text_lower = text.lower() # Simple emotion detection based on keywords emotion_keywords = { "happy": ["happy", "joy", "excited", "great", "wonderful", "amazing"], "sad": ["sad", "sorry", "unfortunate", "disappointing", "regret"], "angry": ["angry", "furious", "mad", "upset", "annoyed"], "excited": ["excited", "thrilled", "amazing", "incredible", "fantastic"], "professional": ["analysis", "report", "data", "research", "study"], "friendly": ["hello", "greetings", "welcome", "nice", "pleasure"] } for emotion, keywords in emotion_keywords.items(): if any(keyword in text_lower for keyword in keywords): return emotion return "neutral" def _adjust_emotion_for_character(self, character: VoiceCharacter, emotion: str) -> str: """Adjust emotion based on character's personality""" emotion_profile = character.emotion_profile # If character has high affinity for this emotion, use it if emotion_profile.get(emotion, 0) > 0.7: return emotion # Otherwise, find the character's strongest emotion strongest_emotion = max(emotion_profile.items(), key=lambda x: x[1])[0] return strongest_emotion async def create_conversation(self, characters: List[str], dialogue: List[str]) -> List[bytes]: """Create a multi-character conversation""" if len(characters) != len(dialogue): raise ValueError("Number of characters must match number of dialogue lines") audio_segments = [] for char_name, line in zip(characters, dialogue): audio = await self.speak_as_character(char_name, line) audio_segments.append(audio) return audio_segments def get_available_characters(self) -> List[str]: """Get list of available character names""" return list(self.characters.keys()) def get_character_info(self, character_name: str) -> Optional[Dict[str, Any]]: """Get detailed information about a character""" if character_name not in self.characters: return None character = self.characters[character_name] return { "name": character.name, "personality": character.personality, "voice_id": character.voice_id, "emotion_profile": character.emotion_profile, "speaking_style": character.speaking_style, "language": character.language } # Example usage and character creation async def create_sample_characters(voice_processor: AdvancedVoiceProcessor): """Create sample characters for demonstration""" # Professor AI - Intelligent and enthusiastic professor_ai = voice_processor.create_character( name="Professor AI", personality={ "traits": ["intelligent", "enthusiastic", "helpful"], "speaking_style": "academic but friendly", "background": "AI researcher and educator" }, voice_id="pNInz6obpgDQGcFmaJgB" # Adam voice ) # Assistant Bella - Friendly and helpful assistant_bella = voice_processor.create_character( name="Assistant Bella", personality={ "traits": ["friendly", "helpful", "calm"], "speaking_style": "warm and approachable", "background": "AI assistant and guide" }, voice_id="EXAVITQu4vr4xnSDxMaL" # Bella voice ) # Commander Charlie - Serious and authoritative commander_charlie = voice_processor.create_character( name="Commander Charlie", personality={ "traits": ["serious", "authoritative", "professional"], "speaking_style": "commanding and clear", "background": "System commander and coordinator" }, voice_id="VR6AewLTigWG4xSOukaG" # Charlie voice ) return [professor_ai, assistant_bella, commander_charlie]