About AiYuga

This company develops and productizes AI models, offering services like text-to-speech, speech recognition, and natural language understanding. Their language models improve recognition accuracy and handle diverse language tasks for clients.

```xml <problem> Current AI models for speech recognition, text-to-speech, and natural language understanding often lack the accuracy and efficiency required for widespread adoption and seamless human-computer interaction. Existing systems struggle to replicate human-level understanding and expression, particularly in nuanced or cross-lingual contexts. </problem> <solution> AI Yuga Algorithms develops and deploys distributed, compact, and efficient AI models focused on bridging the gap between human and machine communication. Their core offerings include text-to-speech with lip synchronization, automatic speech recognition (ASR), and natural language understanding (NLU) systems designed for improved accuracy and scalability. By combining transformers and unsupervised pre-training techniques, AI Yuga aims to create task-agnostic models capable of handling diverse language tasks and replicating human-like understanding. The company leverages neural voices and language models to improve recognition accuracy and generate expressive speech, even cloning target speaker voices with limited data. </solution> <features> - Text-to-speech system capable of cloning target speaker voices with minimal data and controlling prosody and style. - GAN-based generative model and RNN for lip synchronization during speech generation. - Automatic Speech Recognition (ASR) achieving sub 6% Word Error Rate (WER) in certain languages. - Scalable and task-agnostic Natural Language Understanding (NLU) system combining transformers and unsupervised pre-training. - Language models to improve the accuracy of speech recognition. - Cross-language imitation capabilities for text-to-speech, extending beyond simple translation. </features> <target_audience> The primary target audience includes businesses and organizations seeking advanced AI solutions for speech recognition, text-to-speech, and natural language understanding to enhance human-computer interaction and automate language-based tasks. </target_audience> ```

What does AiYuga do?

Where is AiYuga located?

AiYuga is based in Gurugram, India.

When was AiYuga founded?

AiYuga was founded in 2022.

Location

Gurugram, India

Founded

2022

Employees

8 employees

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AiYuga

Score: 23/100

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Executive Summary

aiyuga.com 10+

Founded 2022 – Gurugram, India

Funding

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Team (5+)

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Company Description

Problem

Current AI models for speech recognition, text-to-speech, and natural language understanding often lack the accuracy and efficiency required for widespread adoption and seamless human-computer interaction. Existing systems struggle to replicate human-level understanding and expression, particularly in nuanced or cross-lingual contexts.

Solution

AI Yuga Algorithms develops and deploys distributed, compact, and efficient AI models focused on bridging the gap between human and machine communication. Their core offerings include text-to-speech with lip synchronization, automatic speech recognition (ASR), and natural language understanding (NLU) systems designed for improved accuracy and scalability. By combining transformers and unsupervised pre-training techniques, AI Yuga aims to create task-agnostic models capable of handling diverse language tasks and replicating human-like understanding. The company leverages neural voices and language models to improve recognition accuracy and generate expressive speech, even cloning target speaker voices with limited data.

Features

Text-to-speech system capable of cloning target speaker voices with minimal data and controlling prosody and style.

GAN-based generative model and RNN for lip synchronization during speech generation.

Automatic Speech Recognition (ASR) achieving sub 6% Word Error Rate (WER) in certain languages.

Scalable and task-agnostic Natural Language Understanding (NLU) system combining transformers and unsupervised pre-training.

Language models to improve the accuracy of speech recognition.

Cross-language imitation capabilities for text-to-speech, extending beyond simple translation.

Target Audience

The primary target audience includes businesses and organizations seeking advanced AI solutions for speech recognition, text-to-speech, and natural language understanding to enhance human-computer interaction and automate language-based tasks.