STT and TTS Development Services

Conversations Without Boundaries: Azumo's Voice-First AI Development

Create seamless voice experiences with cutting-edge speech processing technologies developed by Azumo. From crystal-clear transcription to natural-sounding synthesis, our development team builds solutions that enable your applications to hear, understand, and speak with human-like clarity and intelligence.

Introduction

What are Speech to Text and Text to Speech

Azumo builds production-grade speech-to-text and text-to-speech systems for real-time transcription, voice-enabled applications, and multilingual audio processing. Our team developed a generative AI voice assistant for a gaming platform and has built real-time transcription pipelines for enterprise meeting and customer service environments. We work with Whisper, Azure Speech Services, Google Speech-to-Text, and ElevenLabs, selecting engines based on accuracy benchmarks, latency constraints, and language coverage.

Our STT/TTS deployments handle streaming audio, accent and dialect variation, speaker diarization, and low-confidence fallback logic. For text-to-speech, we build custom voice synthesis with controllable tone, pacing, and emotional inflection. All voice AI projects ship with monitoring for transcription accuracy drift and are built under SOC 2 compliance for clients handling sensitive audio data.

The Gap Between Voice AI Promise and Production Reality

Voice technology should make your applications more accessible and your workflows more efficient. Instead, most teams discover that demo-quality transcription collapses in real-world conditions—accents trigger errors, domain vocabulary gets mangled, and synthetic voices still sound uncanny. The gap between benchmark performance and production accuracy costs time, money, and user trust.

Our capabilities
Our Capabilities for STT and TTS Development Services

How We Help You:

Engineering Services

Our Engineering Services for STT and TTS Development Services

Case Study

Voice AI in Production for Our Customers

Speech systems handling real calls in production.

AI Receptionist

Voice AI Development: A Production AI Receptionist on Our Live Phone Line

1.7s
Median Response Time
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Discovery Channel

Developing a natural language based experience for Alexa and Google Home

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Benefits
What You'll Get When You Hire Us for STT and TTS Development Services

Our STT/TTS work includes building a generative AI voice assistant for gaming, real-time transcription systems for enterprise meeting platforms, and custom voice synthesis pipelines for multilingual customer support. We work with Whisper, Azure Speech Services, Google Speech-to-Text, and ElevenLabs, selecting based on your accuracy, latency, and language requirements. For production deployments, we optimize for streaming audio, handle accent and dialect variation, and build fallback logic for low-confidence transcriptions.

Why Choose Us
Why Choose Azumo as Your STT & TTS Development Company
Partner with a proven STT & TTS development company trusted by Fortune 100 companies and innovative startups alike. Since 2016, we've been building intelligent AI solutions that think, plan, and execute autonomously. Deliver measurable results with Azumo.

2016

Building AI Solutions

300+

Successful Deployments

SOC 2

Certified & Compliant

"Behind every huge business win is a technology win. So it is worth pointing out the team we've been using to achieve low-latency and real-time GenAI on our 24/7 platform. It all came together with a fantastic set of developers from Azumo."

Saif Ahmed
Saif Ahmed
SVP Technology
Omnicom

Frequently Asked Questions

  • Azumo builds speech-to-text (STT) and text-to-speech (TTS) systems for real-time transcription, voice-enabled AI assistants, call center analytics, meeting summarization, voice command interfaces, and accessible content generation. We built a generative AI voice assistant for a gaming company that combines real-time speech recognition with LLM-powered dialogue and voice synthesis. Our speech stack includes OpenAI Whisper, Deepgram, and Azure Speech Services for transcription, and ElevenLabs, Azure Neural TTS, Amazon Polly, and open-source models like Coqui TTS for voice synthesis. We deploy on AWS, Azure, and Google Cloud with edge deployment options for low-latency applications. SOC 2 certified with nearshore engineering teams across Latin America.

  • Speech-to-text (STT) converts spoken audio into written text. It handles real-time microphone input and recorded audio files, producing transcripts with speaker identification, timestamps, and punctuation. Text-to-speech (TTS) converts written text into natural-sounding spoken audio. Modern TTS uses neural networks to produce voices that are nearly indistinguishable from human speech, with control over tone, speed, emotion, and accent. Most production voice AI systems use both: STT captures user speech, NLP processes the meaning, the system generates a response, and TTS delivers it as spoken audio. Azumo builds end-to-end voice pipelines that combine STT, NLP/LLM reasoning, and TTS into seamless conversational experiences with sub-second latency for real-time applications.

  • For speech-to-text: OpenAI Whisper (best accuracy across languages and accents), Deepgram (optimized for real-time streaming with speaker diarization), Azure Speech Services (enterprise-grade with custom model training), and Google Cloud Speech-to-Text. For text-to-speech: ElevenLabs (highest quality voice cloning and emotional range), Azure Neural TTS (broadest language coverage with custom voice creation), Amazon Polly (cost-effective for high-volume applications), and open-source models like Coqui TTS and Bark for on-premises deployment. We also work with Twilio and Vonage for telephony integration, WebRTC for browser-based voice, and NVIDIA Riva for GPU-accelerated on-device speech processing.

  • Voice assistants combine three layers: speech recognition (STT), reasoning (NLP/LLM), and voice output (TTS). Azumo builds each layer and optimizes the pipeline for end-to-end latency. The STT layer uses streaming transcription with voice activity detection to capture user speech in real time. The reasoning layer processes transcribed text through an LLM or NLP pipeline that understands intent, retrieves relevant context via RAG, and generates a response. The TTS layer converts the response to speech with appropriate tone and pacing. Total round-trip latency for a conversational voice assistant should stay under 1-2 seconds. We optimize this through model selection, caching, streaming inference, and edge deployment. Our gaming voice assistant project demonstrated real-time generative AI dialogue with natural-sounding voice output.

  • Speech AI delivers strong ROI in healthcare, call centers, media, education, gaming, and accessibility. Healthcare uses STT for clinical dictation and medical transcription, reducing documentation burden on physicians. Call centers automate quality assurance by transcribing and analyzing every call for sentiment, compliance, and coaching opportunities. Media companies use STT for automated captioning, subtitle generation, and content indexing across video libraries. Education platforms use TTS for accessible learning materials and language learning applications. Gaming companies build voice-driven characters and assistants. Accessibility: TTS makes digital content available to visually impaired users. Azumo has built speech AI for gaming and enterprise voice assistant applications.

  • A proof-of-concept voice assistant or transcription system can be delivered in 1-2 weeks using pre-trained models. Production-ready speech AI with custom voice models, enterprise integrations, and real-time latency optimization typically takes 2-4 months. Key timeline factors include audio data quality and availability, custom model training requirements (domain-specific vocabulary, accent handling, custom voice creation), number of integrations, and latency targets. Custom voice creation using voice cloning typically adds 2-4 weeks. Real-time streaming optimization for sub-second latency may require additional tuning. Azumo accelerates delivery with pre-built speech pipelines and Valkyrie for model routing. Our nearshore teams work in US time zones.

  • STT accuracy depends on audio quality, background noise, speaker accents, domain vocabulary, and conversation overlap. Azumo addresses these through model selection (Whisper excels at noisy audio, Deepgram at real-time streaming), custom vocabulary injection for industry-specific terminology (medical terms, legal jargon, product names), speaker diarization to separate overlapping speakers, and noise reduction preprocessing. For domain-critical accuracy, we fine-tune models on your actual audio data. We evaluate STT systems using word error rate (WER) and character error rate (CER) on representative test sets from your environment. Multilingual transcription uses models trained on 100+ languages with automatic language detection. Post-processing pipelines add punctuation, format numbers, and correct common misrecognitions.

  • Azumo is SOC 2 certified and implements end-to-end encryption for audio data at rest and in transit. Voice data is biometric information under GDPR and BIPA (Illinois Biometric Information Privacy Act), requiring explicit consent and careful handling. We build consent management workflows, audio data retention policies, and deletion capabilities to meet regulatory requirements. PII detection runs on transcribed text to redact sensitive information before storage. For healthcare speech AI, we implement HIPAA-compliant audio processing with audit trails and access controls. We offer on-premises deployment for organizations that cannot send audio data to cloud APIs. Voice cloning projects include safeguards against misuse, including watermarking and usage restrictions.