STTNLPUNIFIED APIThe need for a Unified API and reasons to use it instead of directly integrating with Speech To Text providersJohn Jacob
John Jacob5 min read
What is a Unified API?
A single API that lets you connect you to multiple providers and abstracts you away from the peculiarities of integrating with them. This helps software developers integrate with the right service with complete freedom and without additional effort.
Why you should use our Unified API
- Multi-Provider flexibility
Easily compare, switch between, and try out different speech-to-text (STT) and natural language processing (NLP) providers. Mix and match providers based on their performance, pricing, speed, data locality, language and accent support.
No vendor lock-in
Our provider-agnostic format for transcript and transcript metadata storage allows you to build without worrying about provider specific workflows and implementation details.
With our Unified API, you can specify a backup provider. This helps in the instance when your primary provider fails (from an outage etc), and we orchestrate a fallback to backup provider to minimize impact.
Use the right AI engine for the job
Whether mitigating downtime, or benchmarking accuracy, with this API, leveraging the strengths of different providers is now easy. Try out new models and keep up-to-date on new features from different providers.
Effortless ML pipelines built under the hood
Pipeline ASR and NLP tasks by simply stating the tasks you want, and the API will stitch them together while abstracting away provider specific job handling and callback mechanisms.
Standardized transcript formats
Standardized format, with adapters built for each provider, keeping the API maintainable and extensible. Easily add new Providers and functionality that integrate smoothly with the rest of the API and pipelines.
Conversational Intelligence via NLP models Leverage a library of NLP models for a variety of tasks when building conversational apps, and to extract data-driven insights from transcripts.
Extracting the main topics discussed in a transcription, processed by an NLP model.
- Transcript Summary or Summarization
Utilize various summarization systems to obtain transcript summaries that give you a quick and easy way to parse the important points covered in a conversation.
- Entity Detection
Entity Detection, also known as Named Entity Extraction (NER), is an NLP technique where the NLP model identifies and extracts out key entities within the transcript such as company names, product names, numbers, events, and location/dates etc.
- Sentiment Analysis
Sentiment Analysis can help detect emotional value in conversations, by classifying and retrieving positive, negative, and neutral statements in the transcript text.
- Personally Identifiable Information Redaction
PII Redaction can help hide or erase personally identifiable information (PII) content such as name, address, bank account details, ssn etc, from your transcript.
- Question Detection
Sentences in a transcript can be detected as questions by use of a pre-trained NLP model. These detected questions can be used in tandem with other NLP processes, collect metrics, or to solve other business problems.
- Action Items Extraction
Detect action items in the transcript of a recorded meet. The tasks that come up during the meetings are automatically noted, making it for easy follow up.
- Follow Ups Extraction
Like action items, follow-up activities can also be detected and extracted from the transcript of a recorded meet, allowing you to log the intent, schedule a follow up event, or process the intent however you like.
Use our simple speech-to-text API to get all of the advanced AI functionality in one API.
- Batch Transcription
Batch transcription is a service where you may transcribe large audio files, send transcription into storage, query and use stored transcripts via our API.
- Custom Vocabulary
Improve your transcription quality by adding a Custom vocabulary list, that can include words relating to company specific names, domain specific terms, or even colloquial words used by different people around the world.
- Real-Time Transcription
Enable live transcriptions by utilizing our Bot transcription services, that adds a bot to your meeting to live transcribe the meeting on integrated platforms such as Zoom and Google Meet etc.
- Send Bot to Meeting
Send a bot into a live meeting and perform tasks such as live-transcriptions, generate meeting notes, highlight insights all while creating a recording of the meeting.
- Speaker Diarization
The Speaker Diarization feature can break-up an audio recording into segments of detected speakers, giving you information on "who said what" in the transcript text. Each segment in the transcript is labelled with its associated speaker.
- Continual Learning
Analyze generated transcriptions by use of Natural Language Processing (NLP), and achieve continuously improved transcription quality and efficiency.
- Multi Language Support
We provide Multiple Language transcription support.
- Confidence Scores
The Confidence Score specifies the ML / NLP model's certainty of the accuracy of correct predictions made by an algorithm.
- Batch Transcription
ExemplaryAI’s Unified API Directory
Access our Unified-API Directory, connect with Speech-to-text AI engines, and apply ASR, NLP and NLU tasks from a large catalog of providers. We have integrated with the top Speech-to-text/ASR providers in the market, such as AssemblyAI, AWS Transcribe, Azure STT, Deepgram, Google Cloud STT and Nvidia Riva.
We intend to open source our provider adapter layer, making it easy for developers and the community to contribute their own integrations and features. Watch our repository on Github.
Deepgram is an end-to-end Deep Learning Neural Network, that transcribes usable transcriptions, that is continuously improving itself over time. Transcriptions are delivered very quickly, without high hardware or transcription costs. Deepgram is a fast, low cost, and highly scalable api, that provides transcription services such as Speaker Diarization, Summarization, Language/topic detection, and more.
- AWS Transcribe
Amazon Transcribe is an Automatic Speech Recognition (ASR) service, where developers can easily transcribe audio data to text, using Natural Language Processing (NLP) and Machine Learning (ML) models.
AssemblyAI is a Deep Learning software that helps you transcribe and understand your audio data. AssemblyAI is designed to transcribe real time audio, as well as pre-recorded audio and video files. AssemblyAI provides services like Auto Chapters, Sentiment Analysis, Content Safety Detection, Auto Highlights, Entity detection etc.
- Nvidia Riva
Nvidia Riva is a powerful SDK used to build customizable Speech-to-Text applications according to different use-cases. Build and deploy with Riva, where you can adapt and customize your own Conversation AI application, across all platforms.
- Azure Speech-to-text
Azure Cognitive Services provides a Speech-to-Text transcription service feature, that transcribes spoken audio into text format. Azure allows you to quickly transcribe audio into text in over 100 languages, increase accuracy, and enable analytics on the transcribed text.
- Google Cloud Speech-to-Text
With Google AI technology, you can convert speech-to-text using an API. Their API provides benefits such as good accuracy, effortless model customization and flexible deployment.
We hope you will consider using our Unified API to integrate speech to text into your applications and not directly integrate with the providers themselves. For more updates on our Unified-API features, click here.
If you'd like to request an integration, please contact us.