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| import streamlit as st | |
| import torch | |
| from models import build_model | |
| from kokoro import generate | |
| from scipy.io.wavfile import write as write_wav | |
| import os | |
| import re | |
| import numpy as np | |
| from phonemizer import phonemize | |
| from phonemizer.backend.espeak.espeak import EspeakBackend | |
| import subprocess | |
| def load_model(): | |
| device = 'cuda' if torch.cuda.is_available() else 'cpu' | |
| model = build_model('kokoro-v0_19.pth', device) | |
| return model, device | |
| def load_voicepack(voice_name, device): | |
| try: | |
| voicepack = torch.load(f'voices/{voice_name}.pt', weights_only=True).to(device) | |
| return voicepack | |
| except FileNotFoundError: | |
| st.error(f"Errore: La voce '{voice_name}' non è stata trovata.") | |
| return None | |
| def get_espeak_path(): | |
| """Trova il percorso di espeak.""" | |
| try: | |
| result = subprocess.run(['which', 'espeak'], capture_output=True, text=True, check=True) | |
| return result.stdout.strip() | |
| except subprocess.CalledProcessError: | |
| st.error("Errore: espeak non trovato. Assicurati che espeak sia installato e nel PATH.") | |
| return None | |
| def count_tokens(text, lang='en-us'): | |
| """Conta i token di un testo usando phonemizer.""" | |
| espeak_path = get_espeak_path() | |
| if not espeak_path: | |
| return 0 | |
| os.environ['PHONEMIZER_ESPEAK_PATH'] = espeak_path | |
| out_ps = phonemize(text, backend='espeak', language=lang, preserve_punctuation=True, with_stress=True) | |
| ps = ' '.join(out_ps).replace(' ', ' ').strip() | |
| ps = [x for x in ps.split(' ') if x != ''] | |
| return len(ps) | |
| def split_text(text, max_tokens=500, lang='en-us'): | |
| """Suddivide il testo in segmenti più piccoli in base al numero di token.""" | |
| sentences = re.split(r'(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.|\?)\s', text) | |
| segments = [] | |
| current_segment = "" | |
| for sentence in sentences: | |
| sentence_tokens = count_tokens(sentence, lang) | |
| if count_tokens(current_segment, lang) + sentence_tokens <= max_tokens: | |
| current_segment += " " + sentence if current_segment else sentence | |
| else: | |
| if current_segment: # Aggiungi solo se non è vuoto | |
| segments.append(current_segment.strip()) | |
| current_segment = sentence | |
| if current_segment: | |
| segments.append(current_segment.strip()) | |
| return segments | |
| def generate_audio(model, text, voicepack, voice_name): | |
| """Genera audio da testo, gestendo la suddivisione del testo.""" | |
| if voice_name[0] == 'a': | |
| lang = 'en-us' | |
| elif voice_name[0] == 'b': | |
| lang = 'en-gb' | |
| else: | |
| lang = 'en-us' | |
| segments = split_text(text, lang=lang) | |
| all_audio = [] | |
| for segment in segments: | |
| audio, _ = generate(model, segment, voicepack, lang=voice_name[0]) | |
| all_audio.append(audio) | |
| if all_audio: | |
| return np.concatenate(all_audio) | |
| else: | |
| return None | |
| def main(): | |
| st.title("Kokoro TTS Demo") | |
| model, device = load_model() | |
| voice_options = [ | |
| 'af', 'af_bella', 'af_sarah', 'am_adam', 'am_michael', | |
| 'bf_emma', 'bf_isabella', 'bm_george', 'bm_lewis', | |
| 'af_nicole', 'af_sky' | |
| ] | |
| selected_voice = st.selectbox("Seleziona una voce", voice_options) | |
| input_text = st.text_area("Inserisci il testo da convertire in audio:") | |
| if st.button("Genera Audio"): | |
| if not input_text: | |
| st.warning("Inserisci del testo.") | |
| return | |
| voicepack = load_voicepack(selected_voice, device) | |
| if voicepack is None: | |
| return | |
| with st.spinner("Generando audio..."): | |
| audio = generate_audio(model, input_text, voicepack, selected_voice) | |
| if audio is not None: | |
| st.audio(audio, sample_rate=24000) | |
| st.success("Audio generato con successo!") | |
| # Salva l'audio in un file temporaneo | |
| temp_file = "temp_audio.wav" | |
| write_wav(temp_file, 24000, audio) | |
| with open(temp_file, "rb") as f: | |
| st.download_button( | |
| label="Scarica Audio", | |
| data=f, | |
| file_name="output.wav", | |
| mime="audio/wav" | |
| ) | |
| os.remove(temp_file) | |
| if __name__ == "__main__": | |
| main() |