What is NeuralSpace?
NeuralSpace is a Software as a Service (SaaS) platform which offers developers a no-code web interface and a suite of APIs for text and voice Natural Language Processing (NLP) tasks that you can use without having any Machine Learning (ML) or Data Science knowledge.
Along with some of the common languages like English, German, French, etc., the platform supports various languages spoken across India, South East Asia, Africa, the Middle East, Scandinavia and Eastern Europe, aka, low-resource languages. The primary goal of NeuralSpace is to democratize NLP and make sure any developer can create software with advanced text and voice language processing in any language and not just English.
The platform comes with various text and voice processing services that can help you recognize intents and entities in sentences, detect languages, transliterate between alphabets, classify long or short text into categories, identify speakers in a given audio file, transcribe speech into text, and much more. The AI models that power our platform are state-of-the-art, quality assured and ready for you to customize or consume out of the box.
AutoNLP & AutoMLOps
All of our services can be trained/customized using AutoNLP, with which you can build text and voice language processing AI models for your unique use-case. Your models can then be deployed on our cloud infrastructure using AutoMLOps, and you can start using them through APIs with just a few clicks.
The NeuralSpace Platform is designed as a no-code platform for you to take your text and voice language features faster to market and focus on the business problems you are solving, while we take care of all your language processing needs.
Explore Our Services
Whether you are using chatbots, voicebots, or process automation engines, they are all powered by Natural Language Understanding (NLU). It's main purpose is to understand the intent of the user, and extract relevant information (entities) from what they said (voice/speech) or wrote (text) to perform a relevant action. Entities can be anything from names, addresses, account numbers to very domain specific terms like names of chemicals, medicines, etc. NLU can also predict the sentiment of the user which can help analyze user behaviour or create chatbots and voicebots that respond to the user in a more empathetic tone.
- 💻 Service Overview
- 👉 Train, deploy and use your first NLU model in under 5 minutes
Text documents contain key phrases that are useful for making them more easily searchable (e.g., person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages). These categories are called entities. While indexing documents with such meta-information makes them easily accessible, manually extracting them from documents for indexing is extremely laborious and expensive. Additionally, extracting domain-specific terms and phrases requires expert knowledge.
We provide pre-trained entity recognition models for 87 languages but you can also define your own trainable entities.
Whether we are talking about subtitles, government documents or question papers for exams, all of them need to be translated into multiple languages. Manually translating documents at such a scale is not only expensive but also an extremely time-consuming process.
With the help of Translation you can drastically reduce the amount of time to translate documents. Our translation models are all state-of-the-art and can translate text in between more than 100 languages.
For languages that don't use the Latin (English) alphabet, e.g., Arabic, Hindi, Punjabi, Sinhala, typing can be challenging as keyboards/keypads often default to Latin characters. That makes creating content in these vernacular languages difficult. With transliteration you can create content in these languages using your Latin keypad.
For instance, you type a word on the Latin keypad the way you would pronounce it in Punjabi, and using transliteration you can convert that into Punjabi. It transforms a word from one alphabet to the other phonetically.
Any language processing task requires data, and all ML practitioners wish to generate data magically. This was exactly the idea behind building Sentence Generator. Given a sentence, this service can generate up to ten sentences keeping the intent of the original sentence intact. It can help in creating datasets faster and make language processing models more robust.
If the users of your application are multilingual, you naturally have the need to detect which language they are speaking in. This helps you improve your user experience as well as pick language-specific AI models to process what they are saying.
For example, a chatbot can detect the language the user is speaking in and respond in the same language, or an email automation agent can detect the language of the sender and accordingly pick a language-specific AI model to process the rest of the conversation.
- Language Support: Detect over 150 languages directly through our APIs
- Supported Medium: Currently only text documents are supported
Speech To Text (STT)
Speech is the most natural choice of communication for humans. However, current AI models cannot semantically understand speech nearly as well as text. What if you could have a bridge that let's you use speech as an interface while also interpret the meaning behind, to react meaningfully? The Speech To Text (STT) Service is that bridge for you. It is built with state-of-the-art AI models for providing accurate live and file transcriptions of any kind of speech, may it be in conversations or other forms. Once we have transcriptions, it is basically text that can then be meaningfully interpretted by the advanced and battle-tested text services such as Language Understanding.
With the help of Speech To Text, you can exponentially reduce the amount of time it takes for manual transcription of speech audio files.
Text to Speech (TTS)
Text-to-Speech (TTS), also known as voice synthesis or Text-to-Voice, is a technology used to create real-time voice according to custom text. Using NeuralSpace's TTS Service, these synthetic voices can be selected according to your desired language.
With the help of Text-To-Speech, we provide an ideal tool to bridge gaps for your multilingual software and providing worldwide coverage.
Speaker Identification or speech diarization is a process of identifying speakers in audio inputs when more than one person is recorded in the same audio file. Our Speaker Identification Service can help you to separate out different individuals by just uploading an audio file through our APIs.
A common problem in many NLP tasks, especially related to speech in audio files is to separate just the voice audio from the background audio (music, noise, etc.). Whether you want to improve the quality of Speech to Text, or build a video localisation app, or a Karaoke app, you will need a service like this.
Our Voice extraction service was built for this exact purpose.
Sentence Splitter (coming soon)
Sentence spitter (all called tokenization, segmentation, boundary disambiguation) is the process of detecting sentence boundaries, i.e., where the sentence begins and ends. It is considered as a difficult task in NLP because of the ambiguous nature of the punctuation marks. For example, a period does not always show the end of a sentence. It may be a decimal point or represent any abbreviation or email. Moreover, there are many other languages (especially Chinese, Japanese and Urdu) which have an ambiguity in sentence endings, i.e., the sentence sometimes have no definite boundary. This process plays a vital role in text classification, chatbots, language translation, sentimental analysis and many more.
To overcome this issue, we have built the NeuralSpace Sentence Splitter, which can be used to tokenize words and sentences, similar to popular Python library NLTK but for many more languages.
- 👉 APIs coming soon
- 💻 Service Overview
Run on Postman
To kickstart your journey with NeuralSpace we have created a Postman collection that you can fork.