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Amazon Web Services

Lex Speech Recognition

Price per Channel

$60.00

By using Amazon Web Services (AWS) Lex plugin to UniMRCP Server, IVR platforms can utilize AWS Lex API via the industry-standard Media Resource Control Protocol (MRCP) version 1 and 2.

Lex is an AWS service for building conversational interfaces for applications using voice and text. This is the same conversational engine that powers Amazon Alexa.

Natural Language Understanding

Lex provides the deep functionality and flexibility of natural language understanding (NLU) and automatic speech recognition (ASR) so you can build highly engaging user experiences with lifelike, conversational interactions, and create new categories of products.

Simplicity

Lex guides you through using the console to create your own chatbot in minutes. You supply just a few example phrases, and Lex builds a complete natural language model through which the bot can interact using voice and text to ask questions, get answers, and complete sophisticated tasks.

Deep Learning Technologies

Powered by the same technology as Alexa, Lex provides ASR and NLU technologies to create a Speech Language Understanding (SLU) system. Through SLU, Lex takes natural language speech and text input, understands the intent behind the input, and fulfills the user intent by invoking the appropriate business function.

Seamless Deployment and Scaling

With Lex, you can build, test, and deploy your chatbots directly from the Lex console. Lex enables you to easily publish your voice or text chatbots. Lex scales automatically so you don’t need to worry about provisioning hardware and managing infrastructure to power your bot experience.

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Polly Speech Synthesis

Price per Channel

$30.00

By using Amazon Web Services (AWS) Polly plugin to UniMRCP Server, IVR platforms can utilize AWS Polly Text-to-Speech API via the industry-standard Media Resource Control Protocol (MRCP) version 1 and 2.

AWS Polly is a Text-to-Speech service that uses advanced deep learning technologies to synthesize speech that sounds like a human voice.

High Quality

Polly uses best-in-class Text-to-Speech (TTS) technology to synthesize natural speech with high pronunciation accuracy (including abbreviations, acronym expansions, date/time interpretations, and homograph disambiguation).

Low Latency

Polly ensures fast response times, which make it a viable option for low-latency use cases such as dialog systems.

Large Portfolio of Languages and Voices

Polly supports dozens of voices and multiple languages, offering male and female voice options for most languages.

Cloud-based Solution

Text-to-Speech conversion done in the cloud dramatically reduces local resource requirements. This enables support of all the available languages and voices at the best possible quality. Moreover, speech improvements are instantly available to all end-users and do not require additional updates for devices.

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Transcribe Speech Recognition

Price per Channel

$50.00

By using Amazon Web Services (AWS) Transcribe plugin to UniMRCP Server, IVR platforms can utilize AWS Transcribe API via the industry-standard Media Resource Control Protocol (MRCP) version 1 and 2.

Amazon Transcribe uses deep learning to convert speech to text quickly and accurately providing the following main feature:

Easy-to-Read Transcriptions

Amazon Transcribe automatically adds punctuation and formatting so that the output closely matches the quality of manual transcription at a fraction of the time and expense.

Streaming Transcription

You can process audio in batch or in near real-time. Using a secure connection, you can send a live audio stream to the service, and receive a stream of text in response.

Timestamp Generation

Amazon Transcribe returns a timestamp for each word, so that you can easily find a word or phrase in the original recording or add subtitles to video.

Custom Vocabulary

You can add new words to the base vocabulary to generate more accurate transcriptions for domain-specific words and phrases like product names, technical terminology, or names of individuals.

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