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Student startup scoops $2.8M to help Siri respond to locally spoken languages more efficiently

Image credits: NeuralSpace

NeuralSpace, a London-based Natural Language Processing (NLP) company specialising in local or low-resource languages, has secured $2.8M in a seed funding round led by Merus Capital and GoHub Ventures, with participation from APX, Techstars (who also invested in Roleshare, Oper Credits and Simplifyber) and others.

How will the funding be used?

The recent investment will help NeuralSpace to scale its voice AI technology alongside its existing services, which went live earlier this year.

It includes a self-serve toolkit with Language Understanding in 90+ languages and multiple auxiliary functionalities such as automatic data augmentation, automatic data set conversion, language detection to capture a user’s language preference automatically, and translation to convert a user’s input whenever needed for additional context.

How was NeuralSpace born?

In 2017, NeuralSpace grew out of a student project led by two of the founders, Kumar Shridhar and Ayushman Dash, while they studied for their Master’s at TU Kaiserslautern in Germany. Kumar met Felix Laumann in 2018 while he was in Copenhagen working for a, at that time, fresh startup called BotSupply.

The three met for the first time in Berlin shortly afterward, sat a few months later together in Kaiserslautern, and came up with NeuralSpace. Finally, however, they managed to get their first paying customer in November 2019.

Accurate speech models

NeuralSpace aims to develop the most accurate speech models (both Speech-to-Text and Text-to-Speech) for locally spoken languages. Meaning, the platform could allow smart assistant like Google Home, Siri and Alexa to understand more languages.

Further, it develops pre-built end-to-end products such as video localisation (or automatic overdubbing), which are combinations of the existing speech and text services already live on the NeuralSpace Platform as standalone features.

For that, the SaaS platform offers developers a suite of APIs for NLP tasks that can be used without having any machine learning or data science knowledge.

It is a no-code, modular user interface, and each of its services, from Natural Language Understanding (NLU) to Entity Recognition, Speech-to-Text, Machine Translation, and Transliteration can be taken as a standalone product, even installed on-premise if required

The NeuralSpace Platform currently consists of 5 Applications: NeuraLingo, Neural Machine Translation, Transliteration, NeuralAug and Language Detection.

NeuralSpace offers language support for 80+ languages spoken across India, South East Asia, Africa, the Middle East, Scandinavia, and Eastern Europe, aka low-resource languages.

NeuralSpace’s co-founder and CEO Felix Laumann says, “Training latest deep learning models accurately on very small data sets, which any local, low-resource language usually suffers from, is a very challenging task because models are usually designed to perform well in English with terabytes of available text and speech data but not in languages with a few hundred megabytes of data.”

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