83 lines
3.4 KiB
Python
83 lines
3.4 KiB
Python
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"""M0 PoC #2 — TTS bake-off: Azure Neural vs ElevenLabs Flash (§14 Phase 0).
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Synthesizes typical agent sentences with every candidate voice, saves WAVs for
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the founder to listen to, and prints latency + rough per-character cost.
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Env: GOGO_AZURE_SPEECH_KEY / GOGO_AZURE_SPEECH_REGION and/or GOGO_ELEVENLABS_API_KEY.
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Run: python scripts/poc/tts_bakeoff.py [out_dir]
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"""
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from __future__ import annotations
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import asyncio
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import sys
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import time
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parents[2]))
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from gogo.config import get_settings # noqa: E402
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from gogo.voice.audio import pcm_to_wav # noqa: E402
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from gogo.voice.tts import AzureTTS, ElevenLabsTTS # noqa: E402
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SENTENCES = [
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"Dobar dan, dobili ste salon Merima. Ja sam Gogo, virtuelni asistent — razgovor se snima. Kako vam mogu pomoći?",
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"U srijedu poslijepodne slobodno je u dva i trideset ili u pet. Šta vam više odgovara?",
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"Farbanje cijele dužine je od šezdeset do devedeset maraka, zavisno od dužine kose.",
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"Važi. Na koje ime da zavedem zahtjev?",
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"Prosljeđujem salonu zahtjev: šišanje i feniranje, srijeda u pet. Kontaktiraće vas u najkraćem roku radi potvrde. Hvala na pozivu i prijatno!",
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"Izvinite, nisam vas dobro razumio. Možete li ponoviti?",
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]
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AZURE_VOICES = ["sr-RS-SophieNeural", "sr-RS-NicholasNeural", "hr-HR-GabrijelaNeural", "hr-HR-SreckoNeural"]
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ELEVEN_VOICES = ["JBFqnCBsd6RMkjVDRZzb"] # replace with shortlisted hr/sr voices
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# rough public prices (2026): Azure Neural ~$15/1M chars, ElevenLabs Flash ~$50/1M chars
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COST_PER_CHAR_USD = {"azure": 15 / 1_000_000, "elevenlabs": 50 / 1_000_000}
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async def bake(provider_name: str, provider, voices: list[str], out: Path) -> None:
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for voice in voices:
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total_chars = total_ms = 0
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for i, sentence in enumerate(SENTENCES, 1):
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t0 = time.monotonic()
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try:
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pcm = await provider.synthesize(sentence, voice)
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except Exception as e: # noqa: BLE001
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print(f" {voice} #{i}: FAILED — {e}")
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continue
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ms = int((time.monotonic() - t0) * 1000)
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total_chars += len(sentence)
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total_ms += ms
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path = out / f"{provider_name}-{voice.replace(':', '_')}-{i}.wav"
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path.write_bytes(pcm_to_wav(pcm))
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print(f" {voice} #{i}: {ms} ms, {len(pcm) // 16} ms audio → {path.name}")
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if total_chars:
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cost = total_chars * COST_PER_CHAR_USD[provider_name]
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print(
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f" {voice}: avg latency {total_ms // len(SENTENCES)} ms, "
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f"~${cost:.4f} for all {total_chars} chars "
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f"(~${cost / len(SENTENCES) * 1000:.3f} per 1000-char call)\n"
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)
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async def main() -> None:
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out = Path(sys.argv[1] if len(sys.argv) > 1 else "./poc-tts-out")
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out.mkdir(parents=True, exist_ok=True)
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s = get_settings()
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if s.azure_speech_key:
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print("== Azure Neural ==")
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await bake("azure", AzureTTS(), AZURE_VOICES, out)
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else:
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print("(GOGO_AZURE_SPEECH_KEY not set — skipping Azure)")
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if s.elevenlabs_api_key:
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print("== ElevenLabs Flash ==")
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await bake("elevenlabs", ElevenLabsTTS(), ELEVEN_VOICES, out)
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else:
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print("(GOGO_ELEVENLABS_API_KEY not set — skipping ElevenLabs)")
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print(f"\nListen to the WAVs in {out}/ and pick 2–3 voices for the dashboard (§6.1).")
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if __name__ == "__main__":
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asyncio.run(main())
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