Skip to content
Speech Recognition, Synthesis & Voice AI

Speech AI Systems

Custom ASR, TTS, and voice analytics — from real-time transcription to custom voice synthesis — built for accuracy across accents and languages.

Get Started
97%
Transcription Accuracy
50+
Languages Supported
<500ms
Real-Time Latency
20+
Speech AI Projects

Widelly develops speech AI systems that convert spoken language to text, text to natural speech, and enable voice-driven interactions. From high-accuracy transcription and real-time captioning to custom voice synthesis and voice-controlled interfaces, our speech AI solutions are built for production reliability across accents, languages, and noisy environments.

We build custom ASR (automatic speech recognition), TTS (text-to-speech), speaker identification, and voice analytics systems for contact centers, media companies, healthcare providers, and any organization that needs to process, analyze, or generate spoken language at scale.

What We Deliver

Key Capabilities

Speech-to-Text (ASR)

High-accuracy transcription with custom vocabulary, speaker diarization, and real-time streaming support.

Text-to-Speech (TTS)

Natural-sounding voice synthesis with custom voice cloning, emotion control, and multilingual support.

Voice Analytics

Tone, sentiment, and emotion analysis from voice data for contact centers and customer experience.

Speaker Identification

Voiceprint-based speaker recognition for authentication, diarization, and personalization.

Voice Interfaces

Voice-controlled applications and assistants with natural conversation flow and backend integrations.

Applications

Real-World Use Cases

Contact Center Analytics

Voice analytics platform processing 100K+ calls monthly u2014 sentiment scoring, compliance monitoring, and agent coaching.

Medical Dictation System

Custom ASR for clinical notes with medical vocabulary achieving 97% accuracy, integrated with EHR.

Podcast Production AI

Automated transcription, speaker labeling, highlight extraction, and summary generation for media companies.

Why AI

AI-Powered vs Traditional Approach

Aspect Traditional AI-Powered
Transcription Accuracy Generic ASR: 85-90% Custom ASR: 95-97% with domain vocabulary
Voice Quality Robotic, unnatural TTS Natural, expressive voices with emotion control
Domain Adaptation Generic model, no customization Fine-tuned for your terminology and audio
Real-Time Processing Batch only, high latency Streaming with <500ms end-to-end latency
Impact

Business Benefits

Accessibility

Voice interfaces and transcription make products and services accessible to broader audiences.

Efficiency

Automated transcription and voice analytics process hours of audio in minutes.

Customer Insights

Voice analytics reveal customer sentiment, agent performance, and conversation quality at scale.

Custom Voices

Brand-specific voice synthesis creates unique, recognizable voice experiences.

How It Works

Implementation Process

1

Audio Assessment

Analyze your audio data, environment conditions, and accuracy requirements.

2

Model Customization

Fine-tune ASR/TTS models with your domain vocabulary and audio characteristics.

3

Pipeline Development

Build real-time or batch processing pipelines with pre/post-processing.

4

Deployment & Tuning

Deploy with monitoring, accuracy tracking, and continuous improvement.

Technology Stack

Whisper Deepgram Coqui TTS Bark Kaldi PyAnnote WebRTC FFmpeg PyTorch ONNX gRPC WebSocket

Frequently Asked Questions

Generic services like Google/AWS achieve 85-90% on domain content. Custom models fine-tuned on your audio data and vocabulary typically reach 95-97% accuracy.
Yes. We train models with accent-diversified data and noise augmentation. We also build preprocessing pipelines for noise reduction and audio enhancement.
Yes. With as little as 30 minutes of clean audio, we can create custom voice models that sound natural and match the original speaker characteristics.

Ready to Build with AI?

Let's discuss how speech ai systems can transform your business operations.

Book AI Consultation
Get Started →