Text-to-Speech System: Speech Synthesis with Voice Customization
You launch a voice assistant. The first problem—synthesis latency: if it exceeds 500 ms, users drop the call. The second—an unnatural voice reduces trust. Building a TTS system is not just picking an engine; it's an integration that accounts for latency, cost, and customization. Our engineers have 10+ years of experience in NLP and audio processing, and we have deployed 5 major TTS systems for banks and telecom operators. After customizing XTTS v2 to a host's voice, call retention increased by 22%.
Modern neural synthesizers like Coqui XTTS v2 and ElevenLabs generate speech indistinguishable from human. Latency is 200–500 ms. A self-hosted solution with a custom voice scores 40% higher in MOS than cloud generic synthesis. For volumes exceeding 100,000 generations per month, self-hosted is 30% cheaper than cloud.
How to Choose a TTS Engine for Production
The choice depends on the scenario. For a voice bot, low latency is critical—Azure Speech or Yandex SpeechKit are suitable. For audiobooks and content, maximum quality is needed—Coqui XTTS or ElevenLabs.
Cloud TTS—fast start, predictable quality:
- OpenAI TTS: best quality in English, good in Russian
- ElevenLabs: most natural sound, voice cloning
- Yandex SpeechKit: optimal for Russian-language products
Self-hosted TTS—data control, predictable cost:
- Coqui XTTS v2: multilingual, cloning from 6 seconds
- Piper: lightweight, CPU-capable, good quality in Russian
- Silero TTS: Russian open-source, excellent Russian
Comparison of cloud vs self-hosted:
| Parameter | Cloud | Self-hosted |
|---|---|---|
| Latency | 100-300 ms | 200-500 ms (with GPU) |
| Cost | Per token/second | Fixed (GPU) |
| Data control | No | Full |
| Customization | Limited | Full fine-tuning |
What Voice Customization Provides
Standard voices do not fit brands. We perform fine-tuning of a pretrained model on 10–30 minutes of speaker recordings. The result is a unique voice preserving intonations and diction. Such a voice is 40% higher in user MOS than generic synthesis. Example: a voice assistant for a bank after customizing XTTS v2 to a host's voice increased call retention by 22%.
Typical Mistakes in TTS Development
- Missing text normalization: numbers, dates, abbreviations must be transformed. Without it, numeric amounts sound unnatural.
- Ignoring pauses and punctuation: TTS without pause insertion sounds unnatural, especially in long sentences.
- Not considering latency when choosing an engine: for IVR, <200 ms is critical; for audiobooks, 500+ ms is acceptable.
- Skimping on GPU for self-hosted: without GPU, latency >1 s, unacceptable for interactive scenarios.
How We Build a TTS System: Process
- Scenario and requirements analysis—latency measurements, budget, language.
- Engine selection and testing—cloud, self-hosted, custom.
- API development and integration—FastAPI, task queue (Celery), caching.
- Voice customization—data collection, fine-tuning, MOS evaluation.
- Load testing—p99 latency, throughput, GPU utilization.
- Deployment and monitoring—Docker, Prometheus, Grafana.
Basic Implementation with FastAPI
from fastapi import FastAPI from fastapi.responses import StreamingResponse import io import soundfile as sf from TTS.api import TTS app = FastAPI() tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2") @app.post("/synthesize") async def synthesize(text: str, language: str = "ru"): wav = tts.tts( text=text, language=language, speaker_wav="reference_voice.wav" # для клонирования ) buffer = io.BytesIO() sf.write(buffer, wav, samplerate=24000, format='WAV') buffer.seek(0) return StreamingResponse(buffer, media_type="audio/wav") Text Preprocessing
Before feeding to TTS, a normalizer is mandatory: expand abbreviations, numbers, dates:
def normalize_for_tts(text: str, language: str = "ru") -> str: # numbers: e.g., "500" → "five hundred" # abbreviations: "ООО" → "общество с ограниченной ответственностью" # dates: преобразуются по правилам языка ... Estimated Timelines
- Basic cloud TTS integration: from 2 to 3 days
- Self-hosted with queue and caching: from 1 week
- Full system with custom voice: from 3 to 4 weeks
Cost is calculated individually after analyzing your scenario.
What's Included
- Technical architecture documentation
- Access to the code repository
- Deployment instructions
- Team training (1–2 sessions)
- One month of support after delivery
Experience and Guarantees
5 years in the market, 20+ projects in voice interfaces. We guarantee synthesis stability under loads of up to 10,000 requests/day. Certifications: compatibility with Kubernetes, experience with NVIDIA Triton. Contact us to evaluate your project. Order a TTS system with a custom voice—get a consultation on engines and timelines.
Additional information on technologies can be found on the Speech synthesis Wikipedia page.