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DeepPavlov

Bolt custom AI voices onto DeepPavlov-powered agents — turn text-only chatbots into voice-first assistants with sub-second streaming TTS and 90+ language support.

How it works

YOUR APP
DeepPavlov Agent Flow
DeepPavlov chatbot response triggers voice synthesis request via API
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RESEMBLE AI
Streaming TTS
Agent reply synthesized into lifelike AI voice with low latency
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YOUR APP
Deepfake detection
Incoming user audio scanned for synthetic voice spoofing attempts
OUTPUT
Voice assistant
DeepPavlov agents respond with branded, human-sounding speech

Overview

DeepPavlov is the open-source NLP and conversational AI framework used by researchers and product teams to build chatbots, intent classifiers, and dialogue systems. Resemble AI extends those text outputs into speech — a drop-in voice layer that makes any DeepPavlov agent speakable.

Because DeepPavlov already handles multilingual understanding, pairing it with Resemble's 30+ language TTS keeps the full stack consistent: understand the user in their language, respond in the same one, in a voice you designed. Streaming latency under 500 ms keeps the interaction feeling live.

Features

Custom agent voices

Give your DeepPavlov assistant a cloned or designed voice. Stand out from the default-TTS crowd of open-source bots.

Sub-500ms streaming

Stream audio as DeepPavlov generates tokens. Responses start playing immediately, not after the full reply is ready.

Multilingual responses

Speak 90+ languages out of the box. Match DeepPavlov's multilingual NLU with equally multilingual TTS.

Python SDK

Resemble's Python SDK fits naturally into DeepPavlov's Python-first workflow. Add a voice layer in a few lines of code.

Self-hosted friendly

On-prem deployment for teams running DeepPavlov inside their own infrastructure. No mandatory cloud hop.

Research-grade quality

Production-ready 44.1 kHz audio, with emotion and style controls for researchers pushing conversational AI.

Use cases

  • Turn a DeepPavlov chatbot into a voice-first assistant for accessibility use cases
  • Prototype research dialogue systems with a human-sounding voice instead of placeholder TTS
  • Build multilingual voice assistants that understand and respond in the same language
  • Deploy voice-enabled customer agents on-prem for regulated environments
  • Add voice modality to academic conversational AI benchmarks
  • Ship an internal enterprise assistant powered by DeepPavlov with a branded voice

Related integrations

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