AI/ML, AWS, Cloud Computing

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Real Time Speech Processing with Sarvam AI for Indian Languages

Voiced by Amazon Polly

Overview

Players like ElevenLabs, OpenAI, and Google dominate the global speech AI space. While these platforms offer powerful capabilities, they are largely optimized for English and a few major global languages.

India, however, presents a very different challenge, multiple regional languages, code-mixed conversations, and diverse accents. This is where Sarvam AI comes into play with a speech stack designed specifically for Indian use cases.

Instead of offering isolated APIs, Sarvam AI provides a complete speech pipeline that combines Speech-to-Text (STT), Text-to-Speech (TTS), and language processing into a unified system.

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Speech-to-Text (STT): Designed for Real Conversations

Sarvam AI’s STT engine is built to handle how people actually speak in India, not how clean datasets assume they do.

At its core, the system focuses on accuracy in multilingual and informal environments, which is where most traditional models struggle.

What makes it different?

  • 22 Indian languages supported
    Covers major languages like Hindi, Tamil, Telugu, Kannada, Malayalam, Bengali, and Marathi.
  • Code-mixing awareness
    Handles Hinglish, Tanglish, and mixed-language speech naturally.
  • Multiple processing modes
    • Real-time streaming (WebSocket)
    • Batch processing (long audio)
    • REST API (short clips)
  • Speaker diarization
    Identifies who spoke when, useful for meetings, interviews, and call recordings.
  • Low latency (~250 ms)
    Suitable for live conversational systems.

In practice, this means Sarvam’s STT performs well in scenarios like:

  • Call center recordings with mixed Hindi-English conversations
  • Interview transcription with multiple speakers
  • Voice-based applications in regional languages

Unlike generic STT systems, it doesn’t break down when users switch languages mid-sentence, which is extremely common in India.

Text-to-Speech (TTS): Natural, Localized Voice Output

On the output side, Sarvam AI’s TTS engine focuses on naturalness and regional authenticity rather than just clarity.

Many global TTS systems sound polished but often fail to capture the nuances of Indian pronunciation. Sarvam addresses this by training voices specifically for Indian contexts.

Key capabilities

  • Human-like voices tuned for Indian accents
  • Support for 10+ Indian languages
  • Multiple voice styles and tones
  • Context-aware pronunciation (numbers, currency, mixed text)
  • Real-time and batch generation APIs

Latency is also competitive (~800 ms for short responses), making it suitable for:

  • Voice assistants
  • IVR systems
  • Real-time conversational bots

The key advantage here is not just sounding “natural,” but sounding locally correct, which significantly improves user trust and engagement.

Pricing Comparison: Sarvam AI vs ElevenLabs

One of the biggest differentiators for Sarvam AI is pricing, especially for Indian businesses operating at scale.

While ElevenLabs is known for high-quality voice generation and cloning, it comes at a significantly higher cost and is priced in USD.

Sarvam AI Pricing (Approximate)

  • STT: ₹30/hour (~$0.35/hour)
  • STT with diarization: ₹45/hour
  • TTS: ₹15–₹30 per 10,000 characters
  • Free credits: ₹1000 on signup

ElevenLabs Pricing

  • TTS: ~$0.30–$0.60 per 1,000 characters
  • Voice cloning: additional cost
  • Primarily USD-based billing

Cost Difference in Real Terms

When scaled, the difference becomes substantial:

  • Sarvam AI TTS: ~₹15–30 per 10K characters (~$0.18–0.36)
  • ElevenLabs TTS: ~$3–6 per 10K characters

This makes Sarvam 10x–15x cheaper for large-scale deployments, especially in use cases like:

  • Call automation
  • Educational content generation
  • Voice bots handling thousands of users

Additionally, INR pricing avoids:

  • Currency conversion losses
  • Cross-border billing complexities

Why Sarvam AI Stands Out?

Beyond pricing, Sarvam AI’s real strength lies in its alignment with Indian use cases.

  1. India-First Design

Most global models are adapted for India. Sarvam is built for India from the ground up, which reflects in:

  • Better accent handling
  • Stronger performance on regional languages
  • Native support for mixed-language inputs
  1. End-to-End Voice Ecosystem

Instead of stitching together multiple services, Sarvam offers:

  • STT (Speech → Text)
  • TTS (Text → Speech)
  • Translation + Transliteration
  • LLM integration

This reduces architectural complexity when building:

  • Conversational AI systems
  • Voice-based workflows
  • Multilingual assistants
  1. Production-Ready Infrastructure

Sarvam supports:

  • Real-time streaming APIs
  • Batch processing pipelines
  • Enterprise-grade scaling

This makes it suitable for both startups and large-scale enterprise deployments.

  1. Emerging Edge Capabilities

Sarvam is also exploring on-device AI models, which can enable:

  • Offline speech processing
  • Lower latency
  • Improved data privacy

This is particularly valuable for regulated industries like fintech and healthcare.

Limitations to Keep in Mind

Sarvam AI is strong in localization and cost efficiency, but there are areas where global players still lead:

  • Fewer voice customization options
  • Limited voice cloning compared to ElevenLabs
  • Slightly less polished voice realism in some cases

However, these trade-offs are often acceptable when the priority is:

  • Regional accuracy
  • Cost optimization
  • Scalability in Indian markets

When Should You Choose Sarvam AI?

Sarvam AI is a strong fit if your product involves:

  • Indian-language voice assistants
  • Regional customer support automation
  • Interview transcription and analysis
  • Multilingual education platforms
  • Voice-enabled fintech or govtech solutions

If your audience is primarily Indian and multilingual, Sarvam often delivers better real-world performance than global alternatives.

Conclusion

Sarvam AI represents a shift in how speech AI is built, not as a global one-size-fits-all solution, but as a regionally optimized platform.

While platforms like ElevenLabs excel in voice quality and cloning, Sarvam AI leads in:

  • Multilingual Indian support
  • Code-mixed speech understanding
  • Cost efficiency at scale

For businesses targeting India, Sarvam AI is not just a cheaper alternative, it is often the more practical and scalable choice.

Drop a query if you have any questions regarding Sarvam AI and we will get back to you quickly.

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About CloudThat

CloudThat is an award-winning company and the first in India to offer cloud training and consulting services worldwide. As an AWS Premier Tier Services Partner, AWS Advanced Training Partner, Microsoft Solutions Partner, and Google Cloud Platform Partner, CloudThat has empowered over 1.1 million professionals through 1000+ cloud certifications, winning global recognition for its training excellence, including 20 MCT Trainers in Microsoft’s Global Top 100 and an impressive 14 awards in the last 9 years. CloudThat specializes in Cloud Migration, Data Platforms, DevOps, Security, IoT, and advanced technologies like Gen AI & AI/ML. It has delivered over 750 consulting projects for 850+ organizations in 30+ countries as it continues to empower professionals and enterprises to thrive in the digital-first world.

FAQs

1. What is Sarvam AI used for?

ANS: – Sarvam AI is a speech and language AI platform designed primarily for Indian use cases. It enables:

  • Speech-to-Text (STT) transcription
  • Text-to-Speech (TTS) generation
  • Multilingual translation and processing
It is commonly used in voice bots, call centers, interview analysis, and regional language applications.

2. How is Sarvam AI different from ElevenLabs?

ANS: – Compared to ElevenLabs:

  • Sarvam AI is India-first, supporting multiple regional languages
  • It handles code-mixed speech (e.g., Hinglish) better
  • Pricing is significantly lower
  • ElevenLabs offers better voice cloning and premium voice realism

3. Which languages does Sarvam AI support?

ANS: – Sarvam AI supports 20+ Indian languages, including:

  • Hindi
  • Tamil
  • Telugu
  • Kannada
  • Malayalam
  • Bengali
  • Marathi
It also supports automatic language detection and mixed-language inputs.

WRITTEN BY Sidharth Karichery

Sidharth is a Research Associate at CloudThat, working in the Data and AIoT team. He is passionate about Cloud Technology and AI/ML, with hands-on experience in related technologies and a track record of contributing to multiple projects leveraging these domains. Dedicated to continuous learning and innovation, Sidharth applies his skills to build impactful, technology-driven solutions. An ardent football fan, he spends much of his free time either watching or playing the sport.

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